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102
CHAPTER 5
ANALYSIS AND INTERPRETATION
INTRODUCTION
To achieve the objectives of study, the responses obtained through the
questionnaire survey were analyzed using specific statistical tools for socio-
economic variables, customer satisfaction, customer loyalty, customer
retention and perceptions by the customer.
5.1 DEMOGRAPHIC VARIABLES
This study analyzed the demographic variables of the durable white
goods customers on various factors.
5.1.1 Socio-Economic Variables
This section deals with the socio-economic characteristics of the
consumer durable white goods customers in the city of Chennai. The data
presented in the table 5.1 -5.9 depicts the type of residence, age group,
educational level, gender, marital status, number of dependents, stages of the
life cycle and occupation of the respondents duly distributed.
Table: 5.1
Residential Wise Distribution of the Respondents
Sl. No Type of residence Frequency Percentage1. Owned 720 68.62. Rented 280 26.73. Leased 50 4.8
Total 1050 100.0
Source: Field Survey and Analysis of Data 2010
103
Out of the 1050 customers surveyed, 68.6 per cent of the respondents
having own house, 26.7 per cent who residing at rental houses and 4.8 per cent
are taken leased. It is found that majority (68.6 per cent) of the respondents are
residing in own house.
Table: 5.2
Age Wise Classification of the Respondents
Sl.No Age group in years Frequency Percentage
1. 20-30 410 39.0
2. 31-40 460 43.8
3. 41-50 110 10.5
4. 51-60 70 6.7
Total 1050 100.0
Source: Field Survey and Analysis of Data 2010
Table 5.2 shows the distribution of age group of the respondents. Out of
1050 surveyed 43.8 per cent of respondents are under the age group of 31-40
years, 39 per cent are under the age group of 20-30 years, 41-50 years age
group are 10.5 per cent and only 6.7 per cent falls under the age group of 51-
60 years.
720
280
500
100200300400500600700800
Num
ber
ofR
espo
nden
ts
Owned Rented LeasedType of Residence
Figure -5.1 Distributions of Residential Wise Respondents
Frequency
104
Table 5.3
Educational Qualification wise of the Respondents
Sl. No. Educational level Frequency Percentage
1. Higher secondary 150 14.3
2. Under graduate 350 33.3
3. Post graduate 430 41.0
4. Diploma holders 120 11.4
Total 1050 100.0
Source: Field Survey and Analysis of Data 2010
It is found that majority (41.0 percent) of the respondents are post at
graduate levels, 33.3 per cent who have completed under graduate levels, 14.3
per cent who completed higher secondary level and 11.4 per cent of the
respondents are diploma holders.
Figure -5.2 Age Group Wise Distributions
410460
11070
0
100
200
300
400
500
20-30 31-40 41-50 51-60
Num
ber
of
Res
pond
ents
Frequency
Age Group
105
Table.5.4
Gender Wise Distribution of the Respondents
Sl.No Gender Frequency Percentage
1. Male 740 70.5
2. Female 310 29.5
Total 1050 100.0
Source: Field Survey and Analysis of Data 2010
It is found that majority (70.5 percent) of the respondents are male,
remaining 29.5 per cent are female.
Figure 5.3 Educational Wise Distributions of the Respondents
150
350430
120
0
100
200
300
400
500
Highersecondary
Under graduate Post graduate Diploma
Educational level
Frequency
Num
ber o
resp
onde
nts
106
Table 5.5
Distribution of Respondents on Marital Status
Sl.No Marital status Frequency Percentage
1. Unmarried 518 49.3
2. Married 532 50.7
Total 1050 100.0
Source: Field Survey and Analysis of Data 2010
It is clear that 50.7 per cent of the respondents are married and 49.3 per
cent are unmarried.
Figure 5.4 Distribution of Gender
740
310
MaleFemale
107
Table 5.6
Respondents having Number of Dependents
Sl.No Number of dependents Frequency Percentage
1. 1 90 8.6
2. 2 368 35.0
3. 3 432 41.1
4. 4 112 10.7
5. 5 47 4.5
6. 6 1 0.1
Total 1050 100.0
Source: Field Survey and Analysis of Data 2010
Out of the 1050 surveyed, 41.1 per cent of the respondents having three
dependents, 35.0 per cent of the respondents having two dependents,
respondents who are having four dependents 10.7 per cent, 8.6 per cent are
having one dependent, and 0.1 per cent is six and more dependents.
518
532
510515520525530535
Number ofrespondents
Unmarried MarriedStatus
Figure 5.5 Marital Status of the Respondents
Frequency
108
Table 5.7
Stages of the Life Cycle of Respondents
Sl.No. Status of the life cycle Frequency Percentage
1. Newly married 54 10.2
2. Married no children 64 12.0
3. Married and have one or two children 342 64.3
4. Married and have more than two children 72 13.5
Total 532 100.0
Source: Field Survey and Analysis of Data 2010
Table 5.7 shows the respondent stages of their life cycle. It is found that
64.3 per cent are having one or two children, 13.5 per cent more than two
children, 12.0 per cent are married but no children, and 10.2 per cent of the
respondents are newly married couple.
Figure 5.6 Distribution of Dependents of the Respondents
90
368432
11247
10
100
200
300
400
500
1 2 3 4 5 6Number of Dependents
Frequency
109
Table 5.8
Income wise Classification of the Respondents
Sl.No Income group in ` annually Frequency Percentage
1. Under ` 1,00,000 250 23.8
2. `1,00,000 – ` 3,00,000 270 25.7
3. ` 3,00, 000 -` 5,00,000 320 30.5
4. ` 5,00,000 - ` 7,00,000 120 11.4
5. ` 7,00,000- ` 9,00,000 60 5.7
6. ` 9,00,000 and over 30 2.9
Total 1050 100.0
Source: Field Survey and Analysis of Data 2010
Table 5.8 shows the income group of respondents. It is found that out
of 1050 surveyed, 30.5 per cent of the respondents are ` 3,00,000 to
` 5,00,000 income group, 25.7 per cent are coming under the income level of
` 1,00,000 – ` 3,00,000, 23.8 per cent are grouped as under the ` 1,00,000 and
5.7 per cent of the respondents are under the income level of ` 7,00,000-
` 9,00,000, only 2.9 per cent are more than ` 9,00,000 of income annually.
Figure 5.7 Stages of Life Cycle of the Respondents
54
64
342
72
0 100 200 300 400
Newly married
Married no children
Married and have one or twochildren
Married and have more than twochildren
Life Cycle
Number of respondents
Frequency
110
Table 5.9
Occupational wise Distribution of the Respondents
Sl.No Occupation Frequency Percentage
1. Private employee 361 34.4
2. Government employee 270 25.7
3. Professionals 240 22.9
4. Business group 179 17.0
Total 1050 100.0
Source: Field Survey and Analysis of Data 2010
Table 5.9 shows that distribution of the respondents based on their
occupation, 34.4 per cent of the respondents are private employee, 25.7
percentages working as government employee, 22.9 per cent are working as
professional, 17.0 per cent are business people.
250 270320
12060 30
050
100150200250300350
Number ofrespondents
Income group
Figure .5.8 Distribution of Income of the Respondents
Frequency
111
5.2 PURCHASE BEHAVOUR
5.2.1 Various Brands of Durable White Goods Purchased
Table 5.10 shows that responses of various durable white goods brands
are given in column 2, respondents who had purchased their audio brands are
given in column 3, washing machine brands in column 4, air conditioner
brands in column 5 and refrigerator brands in column 6.
361
270240
179
050
100150200250300350400
Number of respondents
PrivateEmployee
GovernmentEmployee
Professionals BusinessGroup
Occupation
Figure 5.9 Occupational Wise Distribution of the Respondents
Frequency
112
Table 5.10
Response of Various Brands of Durable White Goods
Sl.No(1)
Brands(2)
Audio brands (A)(3)
Washing machinebrands(B)
(4)
Air conditionerbrands ( C)
(5)
Refrigeratorbrands( D)
(6)1. Samsung 80
(9.3)220
(24.2)100
(12.5)140
(14.9)
2. LG 70(8.1)
90(9.9)
330(41.2)
160(17.0)
3 Sony 280(32.6)
---
-
4 Aiwa 20(2.3)
-- -
5 Creative 130(15.1)
-- -
6 Philips 160(18.6)
-- -
7 BPL 50(5.8)
10(1.1) --
40(4.3)
8 Onida 30(3.5)
-30
(3.8) -
9 Bosch 20(2.3)
-- -
10 Akai 20(2.3)
-- -
11 Whirlpool--
320(35.2)
10(1.2)
280(29.8)
12. IFB-
160(17.6) - -
13 Videocon--
40(4.4) --
30(3.2)
14 TVS--
10(1.1) - -
15 Godrej--
50(5.5) --
180(19.1)
16 Voltas--
10(1.1)
140(17.5)
20(2.1)
17 General-- --
50(6.2)
-
18 Blue star-- --
70(8.8)
-
113
Table 5.10 continued
19 Carrier-- --
30(3.8)
-
20 Ken star--
--20
(2.5)-
21 National- -
10(1.2)
-
22 Haier- -
10(1.2)
-
23 Alwin-- --
-30
(3.2)
24 Kelvinator- --
--60
(6.4)
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
A: Audio Brands
Table 5.10 shows in column 3, respondents who purchased audio
brands, out of the 1050 surveyed, 32.6 per cent of the respondents having
Sony and 18.6 per cent of the respondents having Philips and least numbers
are Akai and Bosch.
B: Washing Machine Brands
Table 5.10 shows in column 4, respondents who purchased washing
machine brands, it is found that 35.2 per cent of the respondents having
whirlpool and 24.2 percent having Samsung. Lesser number of respondents is
having BPL, TVS and Voltas.
C: Air Conditioner Brands
Table 5.10 shows in column 5, respondents who purchased air
conditioner brands, it is clear that majority (41.2 per cent) of the respondents
having LG, secondly Voltas (67.5 per cent) and least number of respondents is
having Whirlpool, National and Hairer.
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D: Refrigerator Brands
Table 5.10 shows in column 6, respondents who purchased refrigerator
brands, it is found that 29.8 per cent of respondents having Whirlpool,
secondly having Godrej (19.1 per cent).
5.2.2 Factors Considered for Purchase of Durable White Goods
Table 5.11 shows relationship between durable white goods purchased
by the respondents and criteria of brands preference. Column 1 shows criteria.
Column 2 shows the various factors chosen by the respondents to buy the
various brand of white goods. Column 3, 4, 5 and 6 shows audio,washing
machine, air conditioner and refrigerator brands respectively.
Table 5.11
Various Factors Considered while Choosing Durable White Goods
Criteria(1)
Factors(2)
A: Audiobrands
(3)
B:Washingmachinebrands
(4)
C:Airconditioner
brands(5)
D:Refrige-rator
brands(6)
Source ofpurchase
Retail shops 550(64)
520(58.9)
510(63.8)
650(69.1)
Directly from thecompany
50(5.8)
180(20.0)
20(2.4)
40(4.3)
Company showroom 260(30.2)
190(21.1)
270(33.8)
250(26.6)
Source ofinformation
Advertising 350(40.7)
360(40.0)
220(27.4)
390(41.5)
Previous experience 290(33.7)
220(24.4)
290(36.2)
290(30.9)
Recommendations 160(18.6)
260(28.9)
220(27.5)
230(24.5)
Location 40(4.7)
10(1.1)
10(1.2)
10(1.1)
From the internet 20(2.4)
50(5.5)
60(7.55)
20(2.2)
115
Table 5.11 Continued
Enquiredabout thebrand
One shop 210(24.4)
190(21.1)
220(27.5)
300(31.9)
Two shop 270(31.4)
190(21.1)
230(28.85)
270(28.7)
Three shop 230(26.7)
340(37.8)
240(30.0)
230(24.5)
Four shop 90(10.5)
120(13.3)
100(12.5)
60(6.4)
Five shop 40(4.7)
30(3.3)
10(1.2)
50(5.3)
More than 5 20(2.3)
30(3.3)
0 30(3.2)
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
A: Audio Brands
Table 5.11 shows in column 3, 64 per cent of the respondents who
purchased their audio brands from the retail shops, 30.2 per cent are purchased
from the company show room and only 5.8 per cent of them are from the
company as the source of purchase. Regarding source of information 40.7 per
cent the respondents are influenced by advertising, 33.7 per cent of the
respondents are influenced by previous experience with the brand, 18.6 per
cent of the respondents are making purchase recommended by friends,
relatives and neighbors, 4.7 per cent are purchasing the audio brands, where it
is located nearby, only 2.4 per cent of the respondents through active source of
information from the internet. It is found that 31.4 per cent respondents
making enquiry about the audio brands in two shops before purchasing,
followed by 26.7 per cent are enquiring in three shops, 24.4 per cent made
only at one shop, 10.5 per cent of the respondents enquired in four shops, 4.7
per cent and 2.3 per cent have searched the information with more than five
shops.
116
B: Washing Machine Brands
In table 5.11 it is clear that in column 4, majority (58.9 per cent) of the
respondents are purchasing their washing machine brands from the retail
shops, 21.1 per cent are purchasing from the company show room, and only 20
per cent of the respondents directly from the company. It is found that 40.0 per
cent the respondents are influenced by advertising as the major source, 28.9
per cent of the respondents are recommendations from friends, relatives and
neighbors, 24.4 per cent of the respondents are with previous experience with
the brand, 5.5 per cent are purchasing the washing machine brands from active
source of internet and only 1.1 per cent are influenced by nearest location. It
is found that 37.8 per cent respondents making enquiry about the brands in
three shops before purchasing, followed by 21.1 per cent are enquired in two
shops, 21.1 percent are made in one shop, 13.3 per cent have enquired in four
shops , 3.3 per cent made purchase after enquiring in more than five shops.
C: Air Conditioner Brands
In table 5.11 it is clear that column 5, 63.8 per cent of the respondents
who purchased their air conditioner brands from the retail shops, 33.8 per cent
are purchased from the company show room, and only 2.4 per cent of them
purchased their brand from the company. Regarding source of information
36.2 per cent of the respondents are influenced by previous experience with
the air conditioners brand, 27.5 per cent of the respondents are recommended
by friends, relatives and neighbors, 27.4 per cent respondents are influenced to
make a purchase by advertising, 7.55 per cent are making purchase from the
internet, 1.2 per cent purchase from locations nearby. It is also found that 30
per cent respondents made enquiry about the brands in three shops before
purchasing, followed by 28.8 per cent enquired in two shops, 27.5 per cent
made in only one shop, 12.5per cent enquired in four shops, and 1.2 per cent
are in five shops , and no one enquired about more than five shops.
117
D: Refrigerator Brands
In table 5.11 it is clear that in column 6, 69.1 per cent of the
respondents are purchasing refrigerator brand from the retail shops, 26.6 per
cent are purchased from the company show room and only 4.3 per cent of
respondents directly from the company. Regarding source of information 41.5
per cent of the respondents are influenced to make a purchase by advertising,
30.9 per cent of the respondents are influenced by previous experience with
refrigerator brand, 24.5 per cent of the respondents are recommended by
friends, relatives and neighbors, 2.2 per cent are from the internet, 1.1 per cent
purchase by the refrigerator brand located nearby. It is found that 31.9 per cent
respondents making enquiry about the brand in only one shop before
purchasing, followed by 28.7 per cent enquired in two shops, 24.5 respondents
per cent made in three shops, 6.4 per cent enquired in four shops,5.3 per cent
respondents in five shops and only 3.2 per cent enquired in more than five.
Table 5.12 shows that relationship between income group and various
brands audio. Column 1 shows the income group of the respondents and
column 2 to 11 shows the various brands of audio.
Hypothesis 1
H0: There is no significant association between income group of the customers
and brand choice with respect to audio brands.
118
Table 5.12
RELATIONSHIP BETWEEN INCOME GROUP AND VARIOUS
BRANDS OF AUDIO
Incomegroup
(1)
Audio brandsTotalSamsung
(2)LG(3)
Sony(4)
Aiwa(5)
Creative(6)
Philips(7)
BPL(8)
Onida(9)
Bosch(10)
Akai(11)
Less than`.1,00,000
20 10 70 0 40 50 0 0 10 20 220
20.5 17.9 71.6 5.1 33.3 40.9 12.8 7.7 5.1 5.1 220.0
(9.1) (4.5) (31.8) 0 (18.2) (22.7) 0 0 (4.5) (9.1) (100)
`.1,00,000–
` 3,00,000
50 10 50 10 50 40 20 10 0 0 240
22.3 19.5 78.1 5.6 36.3 44.7 14.0 8.4 5.6 5.6 240.0
(20.8) (4.2) (20.8) (4.2) (20.8) (16.7) (8.3) (4.2) 0 0 (100)
`.3,00,000–
` 5,00,000
0 20 100 0 20 60 20 10 0 0 230
21.4 18.7 74.9 5.3 34.8 42.8 13.4 8.0 5.3 5.3 230.0
0 (8.7) (43.5) 0 (8.7) (26.1) (8.7) (4.3) 0 0 (100)
`.5,00,000–
`7,00,000
10 0 50 10 10 0 10 10 0 0 100
9.3 8.1 32.6 2.3 15.1 18.6 5.8 3.5 2.3 2.3 100.0
(10.0) 0 (50) (10) (10) 0 (10) (10) 0 0 (100)
`.7,00,000–
` 9,00,000
0 30 10 0 0 0 0 0 10 0 50
4.7 4.1 16.3 1.2 7.6 9.3 2.9 1.7 1.2 1.2 50.0
0 (60) (20) 0 0 0 0 0 (20) 0 (100)
Greaterthan
`.9,00,000
0 0 0 0 10 10 0 0 0 0 20
1.9 1.6 6.5 .5 3.0 3.7 1.2 0.7 0.5 0.5 20.0
0 0 0 0 (50) (50) 0 0 0 0 (100)
Total 80 70 280 20 130 160 50 30 20 20 860
(9.3) (8.1) (32.6) (2.3) (15.1) (18.6) (5.8) (3.5) (2.3) (2.3) (100)
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
119
Chi square value df Asymp. Sig. (2-sided) Statistical inference
601.9958 45 0.001 P0.001 < 0.05
Significant
Table 5.12 indicates that the various brands of audio among 32.6 per
cent of respondents are having Sony, second Philips (18.6 per cent) and third
creative (15.1 per cent). Least preferred are Akai, Bosch and Aiwa.
The Pearson chi-square value is 601.9958. P- value is lesser than 0.05,
therefore Ho is rejected. Hence it is conclude that, there is a strong association
between the income groups of the customers and brand choice with respect to
audio brands.
Table 5.13 shows the relationship between various income groups of
durable white goods customers and brand choice of washing machine. Column
1 shows the income group of the respondents and column 2-10 are the various
brands of washing machine.
Hypothesis 2
H0: There is no significant association between income group of the customers
and brand choice with respect to washing machine.
120
Table 5.13
RELATIONSHIP BETWEEN INCOME GROUP AND VARIOUS
BRANDS OF WASHING MACHINE
Incomegroup
(1)
Washing machine brandsTotalWhirlpool
(2)LG(3)
IFB(4)
Samsung(5)
Videocon(6)
TVS(7)
Godrej(8)
Voltas(9)
BPL(10)
Less than`.1,00,000
80 30 70 30 0 10 10 0 0 230
80.9 22.7 40.4 55.6 10.1 2.5 12.6 2.5 2.5 230.0
(34.8) (13.0) (30.4) (13.0) 0 (4.3) (4.3) 0 0 (100)
`.1,00,000
– `3,00,000
60 10 70 70 10 0 20 0 0 240
84.4 23.7 42.2 58.0 10.5 2.6 13.2 2.6 2.6 240.0
(25.0) (4.2) (29.2) (29.2) (4.2) 0 (8.3) 0 0 (100)
`.3,00,000
– `5,00,000
110 30 20 60 20 0 10 0 0 250
87.9 24.7 44.0 60.4 11.0 2.7 13.7 2.7 2.7 250.0
(44.0) (12.0) (8.0) (24.0) (8.0) 0 (4.0) 0 0 (100)
`.5,00,000
– `7,00,000
40 20 0 40 10 0 0 0 0 110
38.7 10.9 19.3 26.6 4.8 1.2 6.0 1.2 1.2 110.0
(36.4) (18.2) 0 (36.4) (9.1) 0 0 0 0 (100)
`.7,00,000
– `9,00,000
30 0 0 0 0 0 10 10 10 60
21.1 5.9 10.5 14.5 2.6 .7 3.3 .7 .7 60.0
(50.0) 0 0 0 0 0 (16.7) (16.7) (16.7) (100)
Greaterthan
`.9,00,000
0 0 0 20 0 0 0 0 0 20
7.0 2.0 3.5 4.8 .9 .2 1.1 .2 .2 20.0
0 0 0 (100) 0 0 0 0 0 (100)
Total320 90 160 220 40 10 50 10 10 910
(35.2) (9.9) (17.6) (24.2) (4.4) (1.1) (5.5) (1.1) (1.1) (100)
Source: Field Survey and Analysis of Data 2010. Values within brackets show percentage
121
Chi square value df Asymp. Sig. (2-sided) Statistical inference
585.1902 40 0.001 P0.001 < 0.05
Significant
Table 5.13 indicates the various brands of washing machine. Among
whirlpool having higher (35.2 per cent) respondents, second Samsung (24.26
per cent) and third IFB (17.6 per cent). The least preferred brands are TVS,
Voltas and BPL.
The Pearson chi-square value is 585.1902. P-value is lesser than 0.05,
therefore Ho is rejected. Hence it is conclude that, there is a significant
association between the income group of the customers and brand choice with
respect to washing machine brands.
Table 5.14 shows that relationship between the various income group
of the customers and brands choice of air conditioner. Column 1 shows the
income group of the respondents and column 2-10 shows the various brands of
air conditioner.
Hypothesis 3
H0: There is no significant association between income group of the customers
and brand choice with respect to air conditioner.
122
Table.5.14
RELATIONSHIP BETWEEN INCOME GROUP AND VARIOUS
BRANDS OF AIR CONDITIONER.
Incomegroup
(1)
Air conditioner brands
TotalOnida(2)
Sam-sung(3)
LG(4)
Voltas(5)
General(6)
Bluestar(7)
Whirlpool(8)
Carrier(9)
Kenstar(10)
National(11)
Haier(12)
Less than
`.1,00,000
20 20 100 10 10 30 10 0 0 0 0 200
7.5 25.0 82.5 35.0 12.5 17.5 2.5 7.5 5.0 2.5 2.5 200.0
(10.0) (10.0) (50.0) (5.0) (5.0) (15.0) (5.0) 0 0 0 0 (100)
`.1,00,000–
`3,00,000
0 10 80 40 20 30 0 0 20 10 0 210
7.9 26.2 86.6 36.8 13.1 18.4 2.6 7.9 5.2 2.6 2.6 210.0
0 (4.8) (38.1) (19.0) (9.5) (14.3) 0 0 (9.5) (4.8) 0 (100)
` 3,00,000–
`5,00,000
0 50 110 50 10 0 0 0 0 0 10 230
8.6 28.8 94.9 40.2 14.4 20.1 2.9 8.6 5.8 2.9 2.9 230.0
0 (21.7) (47.8) (21.7) (4.3) 0 0 0 0 0 (4.3) (100)
`.5,00,000–
`7,00,000
10 10 20 10 10 10 0 10 0 0 0 80
3.0 10.0 33.0 14.0 5.0 7.0 1.0 3.0 2.0 1.0 1.0 80.0
(12.5) (12.5) (25.0) (12.5) (12.5) (12.5) 0 (12.5) 0 0 0 (100)
`.7,00,000–
`9,00,000
0 10 0 30 0 0 0 10 0 0 0 50
1.9 6.2 20.6 8.8 3.1 4.4 .6 1.9 1.2 .6 .6 50.0
0 (20) 0 (60) 0 0 0 (20) 0 0 0 (100)
Greaterthan
`.9,00,000
0 0 20 0 0 0 0 10 0 0 0 30
1.1 3.8 12.4 5.2 1.9 2.6 .4 1.1 .8 .4 .4 30.0
0 0 (66.7) 0 0 0 0 (33.3) 0 0 0 (100)
Total30 100 330 140 50 70 10 30 20 10 10 800
(3.8) (12.5) (41.2) (17.5) (6.2) (8.8) (1.2) (3.8) (2.5) (1.2) (1.2) (100)
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
123
Chi square value df Asymp. Sig. (2-sided) Statistical inference
549.764 50 0.001 P0.001 < 0.05
Significant
Table 5.14 indicates the various brands of air conditioners, among
which LG stood first (41.2 per cent) of the respondents purchased, second
Voltas (17.5 per cent) and third Samsung (12.5 per cent). The least preferred
are Whirlpool, National and Haier.
The Pearson chi-square value is 549.764. P-value is lesser than 0.05,
therefore Ho is rejected. Hence it is conclude that, there is a significant
association between the income group of the respondents and brand choice
with respect to air conditioner brands.
Table 5.15 shows the relationship between the various income group of
the customers and brand choice of the refrigerator. Column 1 shows various
income groups of the respondents and column 2-10 are the various brands of
refrigerator.
Hypothesis 4
H0: There is no significant association between income group of the customers
and brand choice with respect to refrigerator brand.
124
Table 5.15
RELATIONSHIP BETWEEN INCOME GROUP AND VARIOUS
BRANDS OF REFRIGERATOR
Incomegroup
(1)
Refrigerator brands
TotalGodrej
(2)Alwin
(3)Kelvinator(4)
Video-con(5)
Voltas(6)
Whirlpool(7) LG(8)
Sam-sung(9)
BPL(10)
Less than`.100000
40 0 10 0 10 60 60 50 0 230
44.0 7.3 14.7 7.3 4.9 68.5 39.1 34.3 9.8 230.0
(17.4) 0 (4.3) 0 (4.3) (26.10 (26.1) (21.7) 0 (100)
`.100000 -`300000
50 0 20 10 0 100 20 20 0 220
42.1 7.0 14.0 7.0 4.7 65.5 37.4 32.8 9.4 220.0
(22.7) 0 (9.1) (4.5) 0 (45.5) (9.1) (9.1) 0 (100)
`.300000 -`500000
70 30 0 0 10 90 40 50 0 290
55.5 9.3 18.5 9.3 6.2 86.4 49.4 43.2 12.3 290.0
(24.1) (10.3) 0 0 (3.4) (31.0) (13.8) (17.2) 0 (100)
`.500000 -`700000
10 0 10 0 0 30 20 20 20 110
21.1 3.5 7.0 3.5 2.3 32.8 18.7 16.4 4.7 110.0
(9.1) 0 (9.1) 0 0 (27.3) (18.2) (18.2) (18.2) (100)
`.700000 -`900000
0 0 20 10 0 0 10 0 20 60
11.5 1.9 3.8 1.9 1.3 17.9 10.2 8.9 2.6 60.0
0 0 (33.3) (16.7) 0 0 (16.7) 0 (33.3) (100)
Greater than`.900000
10 0 0 10 0 0 10 0 0 30
5.7 1.0 1.9 1.0 .6 8.9 5.1 4.5 1.3 30.0
(33.3) 0 0 (33.3) 0 0 (33.3) 0 0 (100)
Total 180 30 60 30 20 280 160 140 40 940
(19.1) (3.2) (6.4) (3.2) (2.1) (29.8) (17.0) (14.9) (4.3) (100)
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
125
Chi square value df Asymp. Sig. (2-sided) Statistical inference
646.6183 40 0.001 P0.001 < 0.05
Significant
Table 5.15 indicates the various brands of refrigerators, among which
Whirlpool stood first (29.8 per cent) of the respondents purchased, second
Godrej (19.1 per cent) and third Samsung (14.9 per cent) followed by other
brands. The least preferred by the respondents is Voltas.
The Pearson chi-square value is 646.6183. P-value is lesser than 0.05,
therefore Ho is rejected. Hence it is conclude that, there is a significant
association between the income group of the customers and brand choice with
respect to refrigerator brands.
5.3 CUSTOMER SATISFACTION
Any customer regarding payments for the product is justified at least
between price of the product and utility, which is greater than what the
payment made by the consumer for the product is called ‘consumer surplus’.
This present analysis deals with how consumer satisfaction with various
attributes for the selective brands. The attributes are shown in column 2 and
column 3-7 shows in rating scales.
5.3.1 Expectations Criteria for Choosing Durable White goods
Table 5.16 to 5.19 represents what is dealt with expectations on various
attributes in availing consumer durable white goods customers.
5.3.1.1 Opinion on Various Criteria Considered for Choosing Audio Brands
Table 5.16 depicts how important the various criteria’s are while
selecting the durable white goods audio brands. Column 2 shows the various
126
criteria’s considered for choosing audio brands and column 3 to 7 shows in
importance scale.
Table 5.16
Opinion on Various Criteria for the Audio brands
SlNo(1)
Criteria (2)
Veryimportant
(3)
Important(4)
Undecided(5)
Lessimportant
(6)
Not at allimportant
(7)
Totalscore
Mean Rank
1 Overall quality 530(61.6)
260(30.2)
60(7.0)
10(1.2) 0 3890 4.52 1
2 Worthiness 380(44.2)
390(45.3)
70(8.1)
20(2.3) 0 3710 4.31 2
3 Responsiveness 230(26.7)
460(53.5)
140(16.3)
30(3.5) 0 3470 4.03 8
4 Warranty 300(34.9)
450(52.3)
40(4.7)
70(8.1) 0 3560 4.10 6
5 Pre –sales 230(26.7)
390(37.1)
110(10.5)
110(10.5)
20(2.3)
3280 3.81 12
6` After salesservice
340(39.5)
420(48.8)
40(4.7)
40(4.7)
20(2.3)
3600 4.18 4
7 Loyaltyprograms
190(22.1)
360(41.9)
190(22.1)
80(9.3)
40(4.7)
3080 3.58 13
8 Sales person’sbehavior
260(30.2)
400(46.5)
70(8.1)
70(8.1)
60(5.7)
3310 3.84 11
9 Repair 240(27.9)
470(54.7)
100(11.6)
50(5.8)
0 3480 4.04 7
10 Reliability 320(37.2)
400(46.5)
90(10.5)
50(5.8)
0 3570 4.15 5
11 Customerservice
510(59.3)
250(29.1)
10(1.2)
20(2.3)
70(8.1)
3690 4.29 3
12 Productcompatibility
240(27.9)
490(57.0)
70(8.1)
40(4.7)
20(2.3)
3470 4.03 8
13 Competitiveprice
240(27.9)
450(52.3)
90(10.5)
50(5.8)
30(3.5)
3400 3.95 10
Source: Field Survey and Analysis of Data 2010Values within brackets show percentage
The importance assigned to the various satisfactions attributes for
durable white goods audio brands are shown in table 5.16. It is understood that
‘overall quality’ is considered to be the prime importance followed by
‘worthiness’ and ‘customer service’. These occupy the second and third place
127
in importance of the audio brands. These are followed by ‘after sales service’,
’reliability’, ‘warranty’,’ repair’, ‘responsiveness’, ‘product compatibility’,
‘competitive price’, ‘sales person’s behavior’ and ‘pre-sales’. The ’loyalty
programs’ are found to be least in importance.
Hence, it is inferred that of all the attributes, importance to audio
brands is maximum for ‘overall quality’.
5.3.1.2 Opinion on Various Criteria Considered for Choosing Washing
Machine Brands
Table 5.17 depicts how important various criteria’s are while selecting
the durable white goods washing machine brands by the customers. Column 2
shows the various criteria’s considered for choosing washing machine brands
and column 3 to 7 shows importance scale.
Table: 5.17
Opinion on Various Criteria for the Washing Machine Brands
Sl.No(1)
Criteria(2)
Veryimpor-
tant(3)
Important(4)
Unde-cided
(5)
Lessimpor-
tant(6)
Not atall
important (7)
Totalscore Mean Rank
1 Overallquality
610(67.0)
280(30.8)
10(1.1)
10(1.1)
04220 4.63 1
2Worthiness
520(57.1)
350(38.5)
10(1.1)
30(3.3)
04090 4.49 3
3 Responsiveness
280(30.8)
520(57.1)
80(8.8)
30(3.3)
03780 4.15 9
4Warranty
460(50.5)
410(45.1)
20(2.2)
20(2.2)
04040 4.43 4
5Pre -sales
380(41.8)
320(35.2)
60(6.6)
130(14.3)
20(2.2)
3640 4.00 10
6` After salesservice
420(46.2)
410(45.1)
30(3.3)
30(3.3)
20(2.2)
3910 4.29 6
7 Loyaltyprograms
230(25.3)
350(38.5)
190(20.9)
100(11.0)
40(4.4)
3360 3.69 13
128
Table No.5.17 continued
8 Salesperson’sbehavior
390(42.8)
300(33.0)
70(7.7)
100(11.0)
50(5.5)
3610 3.96 12
9Repair
380(41.8)
450(49.5)
20(2.2)
60(6.6)
0 3880 4.26 7
10Reliability
470(40.7)
370(35.2)
50(5.5)
10(1.1)
10(1.1)
4010 4.40 5
11 Customerservice
570(62.6)
280(30.8)
50(5.5)
10(1.1)
0 4140 4.54 2
12 Productcompatibility
280(30.8)
250(57.1)
20(2.20
80(8.8)
10(1.1)
3790 4.16 8
13 Competitive price
320(35.2)
390(42.9)
70(7.7)
120(13.2)
10(1.1)
3620 3.97 11
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
The importance assigned to various satisfactions attributes for durable
white goods washing machine brands are shown in table 5.17. It is understood
that ‘overall quality’ is considered to be the prime importance followed by
‘customer service’ and ‘worthiness’. These occupy second and third place in
importance of washing machine brands. These are followed by ‘warranty’,
’reliability’, ‘after sales service’,’ repair’, ‘product compatibility’,
‘responsiveness’ and ‘pre-sales’, ‘competitive price’ and ‘sales person’s
behavior’, The ‘loyalty programs’ are found to be least in importance.
Hence, it is inferred that of all the attributes in the column 2,
importance in washing machine brands is maximum for ‘overall quality’.
5.3.1.3 Opinion on Various Criteria Considered for Choosing Air
Conditioner Brands
Table 5.18 depicts how important the various criteria’s are while
selecting the durable white goods air conditioner brands. Column 2 shows the
various criteria’s considered for choosing air conditioner brands and column 3
to 7 shows importance scale.
129
Table: 5.18
Opinion on Various Criteria for the Air conditioner brands
S. N(1)
Criteria(2)
Veryimpor-
tant(3)
Impor-tant(4)
Undecided
(5)
Lessimpor-
tant(6)
Notat all
impor-tant(7)
Totalscore Mean Rank
1 Overallquality
600(74.1)
180(22.2)
20(2.5)
10(1.2)
03800 4.69 1
2Worthiness
460(56.8)
290(35.8)
30(3.7)
30(3.7)
03610 4.45 2
3 Responsiveness
390(48.1)
350(43.2)
20(2.5)
40(4.9)
10(1.2)
3500 4.32 5
4Warranty
430(53.1)
300(37.0)
40(4.90
40(4.9)
03550 4.38 4
5Pre -sales
230(28.4)
370(45.7)
90(11.1)
100(12.3)
20(2.5)
3120 3.85 11
6` After salesservice
320(39.5)
400(49.4)
50(6.2)
10(1.2)
30(3.7)
3400 4.19 8
7 Loyaltyprograms
240(29.6)
280(34.6)
180(22.2)
70(8.6)
40(4.9)
3040 3.75 13
8 Salesperson’sbehavior
300(37.0)
330(40.7)
60(7.4)
50(6.2)
70(8.6)
3170 3.91 12
9Repair
360(44.4)
360(44.4)
30(3.7)
40(4.9)
20(2.5)
3430 4.23 7
10Reliability
350(43.2)
400(49.4)
40(4.9)
20(2.5)
0 3490 4.30 6
11 Customerservice
420(51.9)
360(44.4)
20(2.5)
10(1.2)
0 3610 4.45 2
12 Productcompatibility
260(32.1)
390(48.1)
70(8.6)
60(7.4)
30(3.7)
3220 3.97 10
13 Competitiveprice
350(43.2)
310(38.3)
60(7.4)
70(8.6)
20(2.5)
3330 4.11 9
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
130
The importance assigned to the various satisfactions attributes for white
goods air conditioner brands are shown in table 5.18. It is understood that
‘overall quality’ is considered to be the prime importance followed by
‘worthiness’ and ‘customer service’. These occupy the second and third place
in importance of air conditioner brands. These are followed by ‘warranty’,
‘responsiveness’, ’reliability’, ‘ repair’, ‘after sales service’, ’competitive
price’,’ product compatibility’, ’pre sales’ and ‘sales person’s behavior’. The
‘loyalty programs’ are found to be least important.
Hence, it is inferred that of all the attributes in column 2 ‘overall
quality’ is of maximum importance in the air conditioner brands.
5.3.1.4 Opinion on Various Criteria Considered for Choosing Refrigerator Brands
Table 5.19 depicts how important are various criteria’s while selecting
the durable white goods refrigerator brands. Column 2 shows the various
criteria’s considered for choosing refrigerator brands and column 3 to 7 shows
on importance scale.
Table: 5.19
Opinion on Various Criteria for the Refrigerator Brands
S.No(1)
Criteria(2)
Veryimpor-tant(3)
Impor-tant (4)
Undeci-ded(5)
Lessimpor-tant (6)
Not at allimpor-tant (7)
Totalscore Mean Rank
1 Overallquality
650(68.4)
250(26.3)
30(3.2)
10(1.1)
10(1.1)
4400 4.63 1
2Worthiness
540(56.8)
340(35.8)
10(1.1)
40(4.2)
20(2.1)
4190 4.41 2
3 Responsiveness
360(37.9)
480(50.5)
70(7.4)
30(3.2)
10(1.1)
4000 4.21 7
4Warranty
410(43.2)
480(50.5)
10(1.1)
40(4.2)
10(1.1)
4090 4.30 4
5Pre -sales
280(29.5)
450(42.9)
120(12.6)
70(7.4)
30(3.2)
3730 3.92 11
6` After salesservice
450(47.4)
400(42.1)
40(4.2)
10(1.1)
50(5.3)
4040 4.25 5
131
Table 5.19 Continued
7 Loyaltyprograms
270(28.4)
370(38.9)
170(17.9)
80(8.4)
60(6.3)
3560 3.74 13
8 Salesperson’sbehavior
230(24.2)
480(50.5)
70(7.4)
120(12.6)
50(5.3)
3570 3.75 12
9Repair
410(43.2)
440(46.3)
20(2.1)
30(3.2)
50(5.3)
3980 4.18 8
10Reliability
370(38.9)
500(52.6)
50(5.3)
10(1.1)
20(2.1)
4040 4.25 5
11 Customerservice
440(46.3)
430(45.3)
40(4.2)
30(3.2)
10(1.1)
4110 4.32 3
12 Productcompatibility
320(33.7)
490(51.6)
40(4.2)
70(7.4)
30(3.2)
3850 4.05 9
13 Competitiveprice
330(34.7)
450(47.4)
70(7.4)
80(8.4)
20(2.1)
3840 4.04 10
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
The importance assigned to the various satisfactions attributes for white
goods refrigerator brands is shown in table 5.19. It is understood that ‘overall
quality ‘is considered to be the prime importance followed by ‘worthiness’
and ‘customer service’. These occupy the second and third place in importance
of the refrigerator brands .These are followed by ‘warranty’, ’reliability’,
‘after sales service’ ,’responsiveness’, ‘repair’, ‘product compatibility’,’
competitive price’ ,’pre- sales’ and sales person’s behavior’. A loyalty
program is found to be least in importance.
Hence, it is inferred that of all the attributes, importance in the
refrigerator brands is maximum for ‘overall quality’.
5.3.2 Various Factors Considered for Satisfaction of Durable White
Goods
Tables 5.20 to 5.23 represent in this section deals with customer
satisfaction on various attributes and their relative importance in availing
consumer durable white goods.
132
5.3.2.1 Level of Satisfaction on Various Attributes with Respect to Audio brands
Table 5.20 depicts the respondents are satisfied with the various
criteria’s by durable white goods audio brands. The various factors of the
satisfaction are shown in column 1 and column 2 to 6 shows rating scale.
Table 5.20
Level of Satisfaction on Various Attributes with Respect to Audio Brands
Factors(1)
Highlysatisfied
(2)
Satisfied(3)
Neutral(4)
Dissatisfied(5)
Highlydissatisfied
(6)
Totalscore Mean Rank
Overall quality440
(51.2)350
(40.7)60
(7.0) 010
(1.0)3790 4.40 1
Worthiness170
(19.8)510
(59.3)140
(16.3)30
(3.5)10
(1.2)3410 3.96 4
Responsiveness230
(26.7)370
(43.0)230
(26.7)20
(2.3)10
(1.2)3370 3.91 5
Warranty200
(23.2)450
(52.3)150
(17.4)60
(7.0) 03370 3.91 5
Usageexperience
240(27.9)
520(60.5)
70(8.1)
30(3.5) 0
3550 4.12 2
Pre –sales230
(26.7)370
(43.0)190
(30.2)60
(7.0)10
(1.2)3330 3.87 9
After salesservice
220(25.6)
410(47.7)
120(14.0)
80(9.3)
30(3.5)
3370 3.91 5
Loyaltyprograms
160(18.6)
400(46.5)
180(20.9)
120(14.0) 0
3180 3.69 14
Sales person’sbehavior
170(19.8)
460(53.5)
170(19.8)
50(4.8)
10(1.2)
3310 3.84 10
Repair180
(20.9)420
(48.8)160
(18.6)70
(8.1)30
(3.5)3230 3.75 13
Reliability240
(27.9)420
(48.8)150
(17.4)50
(5.8) 03430 3.98 3
Customerservice
210(24.4)
440(51.2)
100(11.6)
80(9.3)
30(3.5)
3300 3.83 11
Productcompatibility
150(17.4)
500(58.1)
180(20.9)
20(2.3)
10(1.2)
3340 3.88 8
Competitiveprice
180(20.9)
440(51.2)
160(18.6)
40(4.7)
40(4.7)
3260 3.79 12
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
133
Table 5.20 indicates that most of the respondents are primarily satisfied
with the ‘overall quality’ given by the durable white goods audio brands
followed by the ‘usage experience’, ‘reliability’, ‘worthiness’ which are
considered as a main criteria’s for selecting audio brands. Whereas it is
inferred that from the surveyed respondents they have lower level of
satisfaction with ‘responsiveness’, warranty’,’ after sales service’, ‘product
compatibility’, ‘pre sales’, ‘sale person behavior’, ‘customer service’ and
‘competitive price’. Customers are highly dissatisfied with’ loyalty programs’
offered by the audio brands.
Hence, it is inferred that of all attributes, satisfaction in the audio
brands is maximum for ‘overall quality’.
5.3.2.1.1 Parameters Considered for Selective Brands of Audio
Table 5.21 shows certain parameters assigned for considering the
weighted mean score of audio brands as shown in the column 1 and selective
brands of audio are given in the column 2 to 6 such as Sony, Creative,
Samsung, LG and Philips.
Weighted Mean Score -Audio Brands
Table 5.21
BrandsParameters (1)
Sony(2)
Creative(3)
Samsung(4)
LG(5)
Philips(6)
Overall quality(P1) 4.25 4.38 4.37 5.00 4.56Usage experience(P2) 4.14 4.00 4.12 4.57 4.12Reliability(P3) 3.85 4.00 3.62 4.14 4.25Worthiness(P4) 3.64 3.76 4.00 4.28 4.00Responsiveness(P5) 3.67 3.92 3.85 4.28 3.87Warranty(P6) 3.85 3.84 3.87 4.42 4.18After sales service (P7) 3.67 3.76 3.87 4.28 4.06
Source: Field Survey and Analysis of Data 2010
134
Table 5.21 clearly indicates that the customers are highly satisfied with
the overall quality, usage experience, worthiness, responsiveness, warranty
and after sales service of LG. Philips is highly reliable to the customers
compared to LG, Samsung, Creative and Sony.
Table 5.21-1
BrandsParameters
Sony Creative Samsung LG Philips
Overall quality �
Usage experience �
Reliability �
Worthiness �
Responsiveness �
Warranty �
After sales service �
Figure 5.10
Parameters with Respect to Selective Audio Brands
135
5.3.2.2 Level of Satisfaction on Various Attributes with Respect to
Washing Machine Brands.
Table 5.22 depicts that the customers are satisfied with the various
criteria’s in washing machine brands. The various factors on satisfaction are
given by column 1 and columns 2 to 6 show rating scale.
Table 5.22
Level of Satisfaction on Various Attributes with respect toWashing Machine Brands
Factors(1)
Highlysatisfied
(2)
Satisfied(3)
Neutral(4)
Dissatis-fied(5)
Highlydissatis-
fied(6)
Totalscore Mean Rank
Overallquality
450(49.5)
360(39.6)
60(5.7)
30(3.3)
10(1.1)
3940 4.32 1
Worthiness 300(33.0)
420(46.2)
150(16.5)
30(3.3
10(1.1)
3700 4.06 3
Respon-siveness
240(26.4)
490(53.8)
140(15.4)
30(3.3)
10(1.1)
3650 4.01 5
Warranty 210(23.1)
550(60.4)
100(11.0)
40(4.4)
10(1.1)
3640 4.00 6
Usageexperience
250(27.5)
540(59.3)
80(8).
20(2.2)
20(2.2)
3710 4.07 2
Presales 220(24.2)
410(45.1)
180(17.1)
70(7.7)
30(3.3)
3450 3.79 13
After salesservice
290(31.9)
440(48.4)
90(8.6)
70(7.7)
20(2.2)
3640 4.00 6
Loyaltyprograms
190(20.9)
450(49.5)
160(17.6)
80(8.8)
30(3.3)
3420 3.75 14
Salesperson’sbehavior
200(22.0)
490(53.8)
100(11.0)
90(9.9)
30(3.3)
3470 3.81 11
Repair 280(30.8)
340(37.4)
160(17.6)
100(11.0)
30(3.3)
3470 3.81 11
Reliability 210(23.1)
490(53.8)
100(11.0)
90(9.9)
20(2.2)
3510 3.85 10
Customerservice
290(31.9)
400(44.0)
120(13.2)
40(4.4)
60(6.6)
3550 3.90 9
Productcompatibility
220(24.2)
550(60.4)
100(11.0)
30(3.3)
10(1.1)
3670 4.03 4
Competitiveprice
210(23.1)
530(58.2)
130(14.3)
10(1.1)
30(3.3)
3610 3.96 8
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
136
Table 5.22 indicates that respondents are primarily satisfied with the
‘overall quality’ given by durable white goods washing machine brands
followed by the ‘usage experience’, ‘worthiness’ also considered as a main
criteria for selecting washing machine brands. Whereas it is inferred that the
surveyed respondents have lower level of satisfaction on ‘after sales service’,
‘pre sales’, ‘sale person behavior’, ‘customer service’, ‘competitive price’
‘reliability’ and ‘repair’. They are highly dissatisfied with’ loyalty programs’
offered by washing machine brands.
Hence it is inferred that of all attributes of satisfaction for washing
machine brands ‘overall quality’ is maximum.
5.3.2.2.2 Various Parameters Considered for Washing Machine Brands
Table 5.23 shows certain parameters assigned for determining the
weighted mean score of washing machine brands in column 1 and selective
brands of washing machine are shows in column 2 to 6 such as Whirlpool, LG,
IFB, Samsung and Videocon.
Table 5.23
Washing Machine Brands- Weighted Mean Score
BrandsParameters (1)
Whirlpool(2)
LG(3)
IFB(4)
Samsung(5)
Videocon(6)
Overall quality (P1) 4.12 4.66 4.46 4.22 5.00
Usage experience(P2) 4.12 4.22 4.46 3.72 4.75
Worthiness(P3) 3.84 4.11 4.53 3.90 5.00
Product compatibility(P4) 4.00 4.55 4.40 3.63 4.50
Responsiveness(P5) 3.81 4.11 4.40 4.00 4.00
Warranty(P6) 3.93 4.11 4.00 3.90 4.00
After sales service(P7) 3.84 4.55 4.86 4.09 4.25
137
Table 5.23 indicates that customers are highly satisfied with the overall
quality, usage experience and worthiness of Videocon. Product compatibility
and warranty is high in LG compared to other brands. Consumers feel more
responsive and after sales service for IFB compared to other.
Table 5.23-1
BrandsParameters
Whirlpool LG IFB Samsung Videocon
Overall quality �Usage experience �Worthiness �Product compatibility �Responsiveness �Warranty �After sales service �
Figure 5.11
Parameter with Respect to selective Washing machine Brands
5.3.2.3 Level of Satisfaction on Various Attributes with Respect to Air
Conditioner Brands.
Table 5.24 depicts respondents are satisfied with various criteria’s of
white goods air conditioner brands. The various factors on satisfaction by
respondents are given in column 1 and column 2 to 6 shows rating scale.
138
Table 5.24
Level of Satisfaction on Various Attributes with Respect to Air
Conditioner Brands
Factors(1)
Highlysatisfied
(2)
Satisfied(3)
Neutral(4)
Dissatis-fied(5)
Highlydissatis-fied(6)
Totalscore Mean Rank
Overall quality340
(42.0)320
(39.5)110
(13.6)20
(2.5)20
(2.5)3370 4.16 1
Worthiness 250(30.9)
380(46.9)
100(12.3)
40(4.9)
40(4.9)
3190 3.93 6
Responsiveness250
(30.9)410
(50.6)120
(14.8)0 30
(3.7)3280 4.04 3
Warranty 170(21.0)
500(61.7)
80(9.9)
40(4.9)
20(2.5)
3190 3.93 6
Usageexperience
180(22.2)
460(56.8)
110(13.6)
30(3.7)
30(3.7)
3160 3.90 8
Pre -sales 300(37.0)
260(32.1)
120(14.8)
60(7.4)
70(8.6)
3090 3.81 10
After salesservice
220(27.2)
380(46.9)
110(13.6)
40(4.9)
60(7.4)
3090 3.81 10
Loyaltyprograms
180(22.2)
350(43.2)
200(24.7)
40(4.9
40(4.9)
3020 3.72 13
Sales person’sbehavior
150(18.5)
400(49.4)
150(18.5)
90(11.1)
20(2.5)
3000 3.70 14
Repair 230(28.4)
350(43.2)
120(14.8)
100(12.3)
10(1.2)
3120 3.85 9
Reliability230
(28.4)400
(49.4)120
(14.8)40
(4.9)20
(2.5)3210 3.96 5
Customerservice
220(27.2)
360(44.4)
120(14.8)
30(3.7)
80(9.9)
3040 3.75 12
Productcompatibility
280(34.6)
390(48.1)
60(7.4)
60(7.4)
20(2.5)
3280 4.04 3
Competitiveprice
290(35.8)
420(51.9)
50(6.2)
10(1.2)
40(4.9)
3340 4.12 2
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
In table 5.24, it is found that ‘overall quality’ is the primary criteria for
selecting various brands in air conditioners. It is followed by ‘customer
service’,’ competitive price’, ‘product compatibility’ and ‘responsiveness’ is
139
in fourth place of the scale. It understands that sales person’s behavior is not
that much of a level to satisfy.
Hence, it is inferred that of all attributes on satisfaction for air
conditioner brands ‘overall quality’ is maximum.
5.3.2.3.3 Various Parameters Considered for Selective Brands of Air
Conditioner.
Table 5.25 shows certain parameters assigned for determining the
weighted score of air conditioner brands which is given in the column 1 and
selective brands of air conditioner is given in column 2 to 6 such as Samsung,
LG, Voltas, General and Carrier.
Table 5.25
Air Conditioner Brands –Weighted Mean score
BrandsParameters (1)
Samsung(2)
LG(3)
Voltas(4)
General(5)
Carrier(6)
Overall quality (P1) 4.90 4.15 4.00 3.80 5.00
Competitive price(P2) 3.90 4.18 4.21 4.20 5.00
Productcompatibility(P3)
3.70 4.33 3.92 3.60 4.66
Responsiveness(P3) 3.00 4.15 4.21 4.00 4.33
Reliability(P4) 3.50 4.03 4.21 4.40 3.66
Worthiness(P5) 4.30 4.15 4.15 3.71 3.80
Warranty(P6) 4.10 3.96 3.78 3.80 4.33
Table 5.25 indicates that the customers are highly satisfied with the
overall quality, competitive price, product compatibility, responsiveness and
warranty of Carrier. There is a high reliability in General. Worthiness is more
in Samsung compare to other.
140
Table 5.25-1
BrandsParameters
Samsung LG Voltas General Carrier
Overall quality �
Competitive price �
Product compatibility �
Responsiveness �
Reliability �
Worthiness �
Warranty �
Figure 5.12
Parameters with Respect to Selective Brands of Air Conditioner
5.3.2.4 Level of Satisfaction on Various Attributes with Respect to
Refrigerator Brands.
Table 5.26 depicts that respondents are satisfied with various criteria’s
for refrigerator brands. The various factors on satisfaction are given in column
1 and column 2 to 6 shows rating scale.
141
Table 5.26
Level of Satisfaction on Various Attributes with Respect to
Refrigerator Brands
Factors(1)
Highlysatisfied
(2)
Satisfied(3)
Neutral(4)
Dissatis-fied(5)
Highlydissatis-fied(6)
Totalscore
Mean Rank
Overallquality
450(47.4)
400(42.1)
70(7.4)
10(1.1)
20(2.1)
4100 4.31 1
Worthiness350
(36.8)450
(47.4)110
(11.6)20
(2.1)20
(2.1)3940 4.14 2
Respon-siveness
200(21.1)
540(56.8)
170(17.9)
20(2.1)
20(2.1)
3730 3.92 11
Warranty270
(28.4)540
(56.8)70
(7.4)50
(5.3)20
(2.1)3840 4.04 6
Usageexperience
350(36.8)
430(45.3)
110(11.6)
30(3.2)
30(3.2)
3890 4.09 4
Pre –sales380
(40.0)330
(34.7)120
(12.6)60
(6.3)60
(6.3)3760 3.95 8
After salesservice
360(37.9)
440(46.3)
70(7. 4)
30(3.2)
50(5.3)
3880 4.08 5
Loyaltyprograms
240(25.3)
460(48.4)
160(16.8)
50(5.3)
40(4.2)
3660 3.85 13
Salesperson’sbehavior
180(18.9)
500(52.6)
130(13.7)
110(11.6)
30(3.2)
3540 3.72 14
Repair350
(36.8)370
(38.9)110
(11.6)70
(7.4)50
(5.3)3750 3.94 10
Reliability 350(36.8)
460(48.4)
90(9.5)
20(2.1)
30(3.2)
3930 4.13 3
Customerservice
340(35.8)
380(40.0)
100(1.5)
50(5.3)
80(8.4)
3700 3.89 12
Productcompatibility
240(25.3
550(57.9)
90(8.6)
40(3.8)
30(3.2)
3780 3.97 7
Competitiveprice
270(28.4
530(55.5)
50(5.3)
40(4.2)
60(6.3)
3760 3.95 8
Source: Field Survey and Analysis of Data 2010
Values within brackets show percentage
142
In table 5.26, it is found that ‘overall quality’ is the primary criteria for
selecting white goods refrigerator brands. It is followed by ‘worthiness’,
‘reliability’,’ usage experience’ and ’after sales service is in the fifth place of
the satisfaction scale. Followed with ‘warranty’, product compatibility’,
’competitive price’, ’repair’, responsiveness’ and customer service’. Loyalty
programs offered is highly dissatisfied with ‘sales person’s behavior’.
Hence, it is inferred that of all attributes, satisfaction in refrigerator
brands is maximum for ‘overall quality’.
5.3.2.4.4 Parameters Considered for Selective Brands of Refrigerator.
Table 5.27 shows certain parameters assigned for determining the
weighted score of refrigerator brands is given in column 1 and selective brands
are given in column 2 to 6 such as Godrej, Kelvinator, Whirlpool, LG and
Samsung.
Refrigerator Brands-Weighted Mean Score
Table 5.27
BrandsParameters (1)
Godrej(2)
Kelvinator(3)
Whirlpool(4)
LG(5)
Samsung(6)
Overall quality (P1) 4.38 4.83 4.32 4.25 4.50
Worthiness(P2) 4.44 4.33 3.96 4.06 4.28
Reliability(P3) 4.44 4.66 4.07 4.00 4.00
Usageexperience(P4)
4.33 3.83 4.07 3.87 4.28
After salesservice(P5)
4.44 4.00 4.00 4.12 4.14
Warranty(P6) 4.27 4.00 3.96 4.25 4.00
Productcompatibility(P7)
4.33 3.83 3.64 4.00 3.78
143
Table 5.27 clearly indicates that the customers are highly satisfied with
the overall quality and reliability of Kelvinator. Worthiness, usage experience,
after sales service, warranty period and product compatibility is higher for
Godrej when compared to other brands.
Table 5.27-1
BrandsParameters
Godrej Kelvinator Whirlpool LG Samsung
Overall quality �
Worthiness �
Reliability �
Usage experience �
After sales service �
Warranty �
Product compatibility �
Figure 5.13
Parameter with Respect to Selective Brands of Refrigerator
144
5.3.3 FACTOR ANALYSIS- CUSTOMER SATISFACTION
5.3.3.1 Factor Analysis on Audio Brands
The various attributes considered for factor analysis are overall quality,
worthiness, responsiveness, warranty, usage experience, pre –sales, after sales
service, loyalty programs, sales person’s behavior, repair, reliability, customer
service, product compatibility and competitive price
Factor Analysis –Customer Satisfaction - Audio Brands
Table: 5.28
KMO and Bartlett's test
Kaiser-Meyer-Olkin measure of sampling adequacy. 0.847
Bartlett's test ofsphericity
Approx. Chi-square 5108.59
df 91
Sig. 0.001
Total Variance Explained by Initial Eigen Values
Table 5.29
Component
Initial eigen values
Total Percentage ofvariance Cumulative percentage
1 5.694 40.669 40.669
2 1.375 9.822 50.491
3 1.051 7.509 58.000
Extraction method: Principal component analysis.
145
Table: 5.30
Component matrix ( Without rotation)
AttributesComponent
1 2 3
Overall quality .670 .409 -.069
Worthiness .733 .334 .047
Responsiveness .699 .314 .069
Warranty .538 .241 .610
Usage experience .526 .281 .159
Pre –sales .618 -.484 -.137
After sales service .653 -.351 .023
Loyalty programs .625 -.165 -.165
Sales person’s behavior .558 .182 .026
Repair .674 -.428 .361
Reliability .743 -.188 .108
customer service .584 -.423 -.048
Product compatibility .654 .143 -.577
Competitive price .605 .157 -.343
146
Table: 5.31Varimax Rotated Factor Loading Matrix
AttributesFactor loadings
Communalities(h2)F1 F2 F3
Pre –sales .751 .635
After sales service .685 .550
Loyalty programs .507 .445
Repair .786 .768
Reliability .623 .599
Customer service .690 .522
Overall quality .590 .621
Worthiness .653 .651
Responsiveness .634 .592
Warranty .808 .720
Usage experience .564 .381
Sales person’s behavior .451 .346
Product compatibility .836 .782
Competitive price .625 .508
Eigen values 3.092 2.828 2.200
Percentage of variance explained 22.084 20.199 15.717
Percentage of cumulativevariance explained 22.084 42.283 58.000
Source: Field Survey and Analysis of Data 2010
147
KMO is calculated using correlation and partial correlation to test
whether the variables in our sample are adequate to correlate. A general rule of
thumb is that KMO value should be greater than 0.5 for a satisfaction factor
analysis to proceed, by observing the above results from table 5.28 KMO
value is 0.847; therefore can proceed with factor analysis.
Bartlett’s test of sphericity is to find out the relationship between
variables. A p- value < 0.05 indicates that it makes sense to continue with the
factor analysis, it is found that P is < 0.001, therefore it is concluded that there
are relationships between our variables.
As evident from table 5.29, it is find that 3 factors extracted together
account for 58 per cent of total variance. Hence we have reduced the number
of variables from 14 to 3 underlying factors.
From table 5.31, variables repair loaded as (0.786), pre sales (0.751),
after sales service (0.685), customer service (0.690) and reliability (0.623) on
factor 1. Thus factor 1 can be named as ‘service attributes’.
As for factor 2, it is evident that warranty has the highest load of 0.808
and worthiness be loaded as 0.653, this factor can be termed as ‘product
attributes’.
It is evident that from the table product compatibility has the highest
load of 0.836 and competitive price 0.625, hence this factor can be interpreted
as ‘customer attributes’.
5.3.3.2 Factor Analysis on Washing Machine Brands.
The various attributes considered for factor analysis are overall quality,
worthiness, responsiveness, warranty, usage experience, pre–sales, after sales
service, loyalty programs, sales person’s behavior, repair, reliability, customer
service, product compatibility and competitive price
148
Factor Analysis –Customer Satisfaction – Washing Machine Brands
Table 5.32
KMO and Bartlett's test
Kaiser-Meyer-Olkin measure of sampling adequacy. .893
Bartlett's test of sphericity Approx. Chi-square 7110.005df 91
Sig. .001
Table 5.33
Total Variance Explained by Initial Eigen Values
ComponentInitial eigen values
Total Percentage of variance Cumulative percentage
1 6.980 49.858 49.858
2 1.122 8.012 57.870
Extraction method: Principal component analysis.
Table 5.34
Component matrix ( Without rotation)Attributes 1 2
Overall quality .626 .473
Worthiness .708 .156Responsiveness .758 -.228
Warranty .560 .070
Usage experience .680 .488Pre –sales .795 -.096
After sales service .716 -.346Loyalty programs .751 -.073
Sales person’s behavior .655 -.240
Repair .663 -.452Reliability .817 -.144
customer service .659 .251Product compatibility .698 .311
Competitive price .756 -.043
149
Table 5.35
Varimax Rotated Factor Loading Matrix
Attributes
Factor Loadings
Communalities(h2)F1 F2
Responsiveness .720 .627
Warranty .373 .318
Pre -sales .660 .641
After sales service .766 .632
Loyalty programs .612 .569
Sales person’s behavior .650 .486
Repair .796 .644
Reliability .708 .688
Competitive price .596 .574
Overall quality .769 .616
Worthiness .585 .525
Usage experience .815 .700
customer service .624 .497
Product compatibility .695 .584
Eigen values 4.418 3.684
Percentage of variance explained 31.555 26.315
percentage of cumulative variance
explained31.555 57.870
Source: Field Survey and Analysis of Data 2010
KMO is calculated using correlation and partial correlation to test
whether the variables in our sample are adequate to correlate. A general rule of
thumb is that KMO value should greater than 0.5 for a satisfaction factor
analysis to proceed, by observing the above results from table 5.32 KMO
value is 0.893; therefore we can proceed with factor analysis.
150
Bartlett’s test of sphericity is to find out the relationship between the
variables. A p- value is < 0.05 indicates that it makes sense to continue with
the factor analysis, it is found that P is < 0.001, therefore it is concluded that
there are relationships between our variables.
As evident from table 5.33, found that 2 factors extracted together
account for 57.87 per cent of total variance. Hence we have reduced the
number of variables from 14 to 2 underlying factors.
From table 5.35, variables repair loaded as (0.796), reliability (0.708),
responsiveness (0.720), after sales service (0.766) and sales person’s behavior
on factor 1. Thus factor 1 can be named as ‘service attributes’.
As for factor 2, it is evident that usage experience has the highest load
of 0.815 and overall quality’ be loaded as 0.769 and product compatibility
(0.695), this factor can be termed as ‘customer experience’.
5.3.3.3 Factor Analysis on Air Conditioner Brands.
The various attributes considered for factor analysis are overall quality,
worthiness, responsiveness, warranty, usage experience, pre –sales, after sales
service, loyalty programs, sales person’s behavior, repair, reliability, customer
service, product compatibility and competitive price.
Factor Analysis –Customer Satisfaction – Air Conditioner Brands
Table: 5.36
KMO and Bartlett's test
Kaiser-Meyer-Olkin measure of sampling adequacy. .860
Bartlett's test of sphericity Approx. Chi-square 7719.045
Df 91
Sig. .001
151
Table: 5.37
Total Variance Explained by Initial Eigen Values
ComponentInitial eigen values
Total Percentage of variance Cumulative percentage
1 7.202 51.442 51.442
2 1.432 10.226 61.669
3 1.029 7.350 69.019
Extraction method: Principal component analysis.
Table 5.38
Component matrix ( Without rotation)
Attributes 1 2 3
Overall quality .610 .669 .122
Worthiness .747 .480 .208
Responsiveness .687 .181 -.165
Warranty .745 .185 -.255
Usage experience .723 .470 .165
Pre –sales .765 -.236 -.059
After sales service .839 -.131 -.114
Loyalty programs .716 -.060 -.524
Sales person’s behavior .660 -.131 -.289
Repair .775 -.275 -.240
Reliability .673 -.298 .266
customer service .687 -.206 .189
Product compatibility .715 -.252 .329
Competitive Price .671 -.320 .452
152
Table: 5.39
Varimax Rotated Factor Loading Matrix
Attributes
Factor loadings
Communalities(h2)F1 F2 F3
Responsiveness .522 .531
Warranty .626 .655
Pre -sales .568 .644
After sales service .636 .733
Loyalty programs .857 .791
Sales person’s behavior .656 .536
Repair .718 .733
Reliability .715 .612
Customer service .629 .550
Product compatibility .756 .684
Competitive price .841 .757
Overall quality .894 .834
Worthiness .826 .832
Usage experience .796 .772
Eigen values 3.470 3.282 2.911
Percentage of variance explained 24.783 23.441 20.795
Percentage of cumulative variance 24.783 48.224 60.019
Source: Field Survey and Analysis of Data 2010
153
KMO is calculated using correlation and partial correlation to test
whether the variables in our sample are adequate to correlate. A general rule of
thumb is that KMO value should greater than 0.5 for a satisfaction factor
analysis to proceed, by observing the above results from table 5.36 KMO
value is 0.860; therefore we can proceed with factor analysis.
Bartlett’s test of sphericity is to find out the relationship between the
variables. A p- value < 0.05 indicates that it makes sense to continue with the
factor analysis, we found that P is < 0.001, therefore it is concluded that there
are relationships between our variables.
As evident from table 5.37, we find that 3 factors extracted together
account for 69 per cent of total variance. Hence we have reduced the number
of variables from 14 to 3 underlying factors.
From table 5.39, variables loyalty programs loaded as (0.857), repair
(0.718), sales person behavior (0.656), and after sale service (0.636) on factor
1. Thus factor 1 can be named as ‘customer loyalty’.
As for factor 2, it is evident that competitive price has the highest load
of 0.841, product compatibility’ (0.756) and reliability be loaded as 0.715, this
factor can be termed as ‘price attributes’.
It is evident that from the table, that overall quality has the highest load
of 0.894, worthiness 0.826,and usage experience 0.796, hence this factor can
be interpreted as ‘product attributes’.
5.3.3.4 Factor Analysis on Refrigerator Brands
The various attributes considered for factor analysis are overall quality,
worthiness, responsiveness, warranty, usage experience, pre –sales, after sales
service, loyalty programs, sales person’s behavior, repair, reliability, customer
service, product compatibility and competitive price.
154
Factor Analysis –Customer Satisfaction - Refrigerator BrandsTable 5.40
KMO and Bartlett's test
Kaiser-Meyer-Olkin measure of sampling adequacy. .917
Bartlett's test of sphericity Approx. Chi-square 9308.44
Df 91
Sig. .001
Table 5.41
Total Variance Explained by Initial Eigen Values
Component Initial eigen values
Total Percentage of variance Cumulative percentage
1 7.988 57.060 57.060
2 1.004 7.171 64.231
Extraction method: Principal component analysis.
Table 5.42
Component matrix ( Without rotation)
Attributes 1 2Overall quality .681 .422
Worthiness .764 .249
Responsiveness .705 .403Warranty .760 -.091
Usage experience .762 -.053Pre –sales .731 .183
After sales service .802 .023
Loyalty programs .775 .090Sales person’s behavior .790 -.114
Repair .732 -.321
Reliability .773 .007csutomer service .794 .141
Product compatibility .779 -.372Competitive price .717 -.524
155
Table 5.43
Varimax Rotated Factor Loading Matrix
AttributesFactor loadings
Communalities(h2)F1 F2
1 2Overall quality .784 .642Worthiness .724 .645Responsiveness .787 .658Reliability .563 .597Customer service .671 .651Pre –sales .654 .568After sales service .595 .643Loyalty programs .622 .608Warranty .592 .586Usage Experience .566 .583Sales person’s behavior .629 .638Repair .738 .639Product compatibility .807 .745Competitive Price .874 .789Eigen values 4.646 4.346Percentage of variance explained 33.185 31.045Percentage of Cumulative varianceexplained 33.185 64.231
Source: Field Survey and Analysis of Data 2010
KMO is calculated using correlation and partial correlation to test
whether the variables in our sample are adequate to correlate. A general rule of
thumb is that KMO value should greater than 0.5 for a satisfaction factor
analysis to proceed, by observing the above results from table 5.40 KMO
value is 0.917; therefore we can proceed with factor analysis.
Bartlett’s test of sphericity is to find out the relationship between the
variables. A p- value < 0.05 indicates that it makes sense to continue with the
156
factor analysis, it is found that P is < 0.001, therefore it is concluded that there
are relationships between our variables.
As evident from table 5.41, it is found that 2 factors extracted together
account for 64.23 per cent of total variance. Hence we have reduced the
number of variables from 14 to 2 underlying factors.
From table 5.43, variables responsiveness loaded as (0.787), overall
quality (0.784), worthiness (0.724) and customer service (0.671) on factor 1.
Thus factor 1 can be named as ‘customers response attributes’.
As for factor 2, it is evident that competitive price has the highest load
of 0.874 and product compatibility’ be loaded as 0.807 and repair 0.738, this
factor can be termed as ‘product attributes’.
5.3.4 REGRESSION MODEL ON CUSTOMER SATISFACTION OF
CONSUMER DURABLE WHITE GOODS
An in-depth study of satisfaction would not be complete without the
identification of key indicators of customer’s satisfaction.
Assuming the existence of linear relationship between the independent
variables and dependent variable, multiple regression analysis is done between
level satisfaction of different predictor variables of satisfaction and overall
satisfaction of service.
5.3.4.1 Regression Model on Satisfaction Audio Brands
This study attempted to develop a model to analyze satisfaction of
audio brands. Enter method of regression analysis of satisfaction (Y) is
performed with the variables X1- overall quality ; X2- worthiness, X3-
responsiveness; X4- warranty ; X5- usage experience; X6- pre-sales;X7-after
sales service;X8- loyalty programs; X9-sales persons behaviour;X10-
repair,X11- reliability;X12- customer service X13-product compatibility X14-
competitive price for the audio brands.
157
Table 5.44
Regression Model-Satisfaction-Audio Brands
Model R R square Adjusted R Square Std. error of the estimate
1 .829 .687 .681 .230
ANOVAModel Sum of squares df Mean square F Sig.
1 Regression 97.709 14 6.979 132.182 .001
Residual 44.616 845 .053
Total 142.326 859
Coefficients
ModelUn standardized
coefficientsStandardizedcoefficients t Sig.
(P value)B Std. Error Beta
1 (Constant) 3.519 .064 54.958 .001
Overall quality -.103 .017 -.183 -6.212 .001
Worthiness -.020 .016 -.038 -1.238 .216
Responsiveness -.031 .013 -.064 -2.321 .020
Warranty .008 .012 .016 .655 .512
Usage experience -.071 .014 -.122 -5.274 .001
Pre -sales -.033 .012 -.074 -2.846 .005
After sales service -.038 .011 -.095 -3.510 .001
Loyalty programs .002 .011 .004 .167 .867
Sales person’s behavior -.074 .011 -.153 -6.686 .001
Repair -.043 .012 -.104 -3.479 .001
Reliability -.097 .014 -.198 -6.921 .001
Customer service -.114 .010 -.284 -10.917 .001
Product compatibility .043 .016 .079 2.740 .006
Competitive price -.006 .011 -.016 -.589 .556
Source: Field Survey and Analysis of Data 2010 Level of significance (0.05%)
158
The R value (0.829) indicates multiple correlation coefficients between
all the entered independent variables and dependent variables.
The R square value in model summary table shows the portion of
variance accounted for by the independent variables that are approximately 69
per cent of variance in satisfaction accounted for.
The ANOVA table indicates p-level to be 0.001.This indicates that the
model is statistically significant at a confidence level of 99.999. The P-level
indicates the significance of the F- value.
Also note that t- tests significance of individual independent variables
indicate that overall quality, usage experience, pre sales, after sales service,
sales person’s behavior, repair, reliability, customer service and product
compatibility are independent variables which are statistically significant in
this model.
The standardized coefficients Beta column, gives the coefficients of
independent variables in the regression equation including all predictor
variables.
Satisfaction Y = -0.183X1 -0.038X2-0.064 X3+0.016X4-0.122 X5-0.074X6-
0.095X7+0.004X8-.153X9-.104X10-0.198X11-0.284X12+0.079X13-0.016X14. (5.1)
5.3.4.2 Regression Model on Satisfaction Washing Machine Brands
This study attempted to develop a model to analyze satisfaction of
washing machine brands. Enter method of regression analysis of satisfaction
(Y) is performed with the variables X1- overall quality ; X2- worthiness, X3-
responsiveness; X4- warranty ; X5- usage experience; X6- pre-sales;X7-after
sales service;X8- loyalty programs; X9-sales persons behaviour;X10-
repair,X11- reliability;X12- customer service X13-product compatibility X14-
competitive price for the washing machine brands.
159
Table 5.45
Regression Model-Satisfaction Washing Machine Brands
Model R R squareAdjusted R
squareStd. error of the estimate
1 .810 .656 .650 .261
ANOVA
Model Sum ofsquares df Mean square F Sig.
1 Regression 115.829 14 8.274 121.642 .001
Residual 60.874 895 .068
Total 176.703 909
Coefficients
ModelUn standardized
coefficientsStandardizedcoefficients t Sig.(P value)
B Std. error Beta
1 (Constant) 2.898 .064 45.098 .001
Overall quality .010 .015 .018 .658 .510
Worthiness -.014 .015 -.027 -.948 .343
Responsiveness -.057 .017 -.104 -3.249 .001
Warranty .094 .014 .167 6.737 .001
Usage experience -.018 .016 -.032 -1.112 .266
Pre-sales -.035 .014 -.080 -2.449 .015
After sales service -.005 .013 -.011 -.375 .708
Loyalty program -.054 .014 -.120 -3.869 .001
Salesperson’sbehavior
.007 .012 .016 .599 .549
Repair -.049 .011 -.121 -4.342 .001
Reliability -.152 .016 -.330 -9.344 .001
customer service -.119 .011 -.296 -11.079 .001
Productcompatibility
-.051 .017 -.088 -2.942 .003
Competitive price .019 .017 .036 1.083 .279
Source: Field Survey and Analysis of Data 2010 Level of significance (0.05%)
160
The R value (0.810) indicates multiple correlation coefficients between
all the entered independent variables and dependent variables.
The R square value in the model summary table shows the portion of
variance accounted for by the independent variables that is approximately 66
per cent of variance in satisfaction is accounted for.
The ANOVA table indicates the p-level to be 0.001.this indicates that
the model is statistically significant at a confidence level of 99.999. The P-
level indicates the significance of the F- value.
Also note that t- tests significance of individual independent variables
indicate that responsiveness, warranty, loyalty program, repair, reliability,
customer service, product compatibility are the independent variables which
are statistically significant in the model.
The standardized coefficients Beta column, gives the coefficients of
independent variables in the regression equation including all predictor
variables.
Satisfaction Y =.018X1-.027X2-.104X3+.167X4-.032X5-.080X6-.011X7-.120X8+.016X9-
.121X10-.330X11-.296X12-.088X13+.036X14 (5.2)
5.3.4.3Regression Model on Satisfaction for the Air Conditioner brands
This study also attempted to develop a model to analyze satisfaction of
air conditioner brands. Enter method of regression analysis of satisfaction (Y)
is performed with the variables X1- overall quality ; X2- worthiness, X3-
responsiveness; X4- warranty ; X5- usage experience; X6- pre-sales;X7-after
sales service;X8- loyalty programs; X9-sales persons behaviour;X10-
repair,X11- reliability;X12- customer service X13-product compatibility X14-
competitive price for the air conditioner brands.
161
Table 5.46
Regression model- Satisfaction-Air conditioner Brands
Model R R square Adjusted R square Std. error of the estimate1 .892 .796 .792 .208
ANOVA
Model Sum of Squares dfMean
Square F Sig.
1 Regression 134.444 14 9.603 221.648 .001
Residual 34.444 795 .043Total 168.889 809
Coefficients
ModelUn standardized coefficients Standardized
coefficients t Sig.(pvalue)
B Std. Error Beta1 (Constant) 2.983 .050 60.163 .001
Overall quality .029 .014 .059 2.166 .031
Worthiness -.054 .014 -.121 -3.935 .001Responsiveness .042 .013 .083 3.275 .001
Warranty -.018 .014 -.033 -1.287 .198Usage experience -.003 .015 -.005 -.185 .853
Pre-sales -.048 .009 -.130 -5.125 .001
After sales service -.047 .014 -.115 -3.398 .001Loyalty program -.108 .014 -.240 -7.939 .001Salesperson’sbehavior .032 .012 .068 2.610 .009
Repair -.049 .013 -.108 -3.830 .001
Reliability -.098 .011 -.198 -8.695 .001
Customer service -.150 .009 -.388 -16.146 .001Productcompatibility -.088 .012 -.186 -7.356 .001
Competitive price .109 .012 .227 9.206 .001
Source: Field Survey and Analysis of Data 2010 Level of significance (0.05%)
The R value (0.892) indicates the multiple correlation coefficients
between all the entered independent variables and dependent variables.
162
The R square value in the model summary table shows the portion of
variance accounted for by the independent variable that is approximately 80
per cent of variance in satisfaction which is accounted for.
The ANOVA table indicates the p-level to be 0.001.this indicates that
the model is statistically significant at a confidence level of 99.999. The P-
level indicates the significance of the F- value.
Also note that t- tests significance of individual independent variables
indicate that worthiness, responsiveness, pre-sales, after sales service, loyalty
programs, repair, customer service, product compatibility, competitive price
are the independent variables which are statistically significant in the model.
The standardized coefficients Beta column, gives the coefficients of
independent variables in the regression equation including all predictor
variables.
Y =.059 X1-.121 X2+.083 X3-.033X4-.005X5-.130X6-.115X7-.240X8+.068X9-.108X10-
.198X11-.388X12-.186X13+.227X14 (5.3)
5.3.4.4 Regression Model on Satisfaction Refrigerator brands
The study also attempted to develop a model to analyze satisfaction of
refrigerator brands. Enter method of regression analysis of satisfaction (Y) is
performed with the variables X1- overall quality ; X2- worthiness, X3-
responsiveness; X4- warranty ; X5- usage experience; X6- pre-sales;X7-after
sales service;X8- loyalty programs; X9-sales persons behaviour;X10-
repair,X11- reliability;X12- customer service X13-product compatibility X14-
competitive price for the refrigerator brands.
163
Table 5.47
Regression Model-Satisfaction-Refrigerator Brands
Model R R square Adjusted Rsquare Std. error of the estimate
1 .456 .208 .196 .546
ANOVA
ModelSum ofsquares
dfMeansquare
F Sig.
1 Regression 73.096 14 5.221 17.490 .001
Residual 279.114 935 .299
Total 352.211 949
Coefficients
ModelUn standardized
coefficientsStandardizedcoefficients
t Sig.B Std. Error Beta
1 (Constant) 1.662 .114 14.633 .001
Overall quality .073 .031 .099 2.349 .019
Worthiness -.088 .033 -.124 -2.701 .007
Responsiveness -.121 .032 -.162 -3.749 .001
Warranty .157 .031 .224 5.105 .001
Usage experience -.128 .029 -.198 -4.410 .001
Pre-sales .019 .024 .037 .807 .420
After sales service -.108 .033 -.182 -3.261 .001
Loyalty program .194 .031 .317 6.304 .001
Salesperson’s behavior -.031 .030 -.050 -1.026 .305
Repair -.209 .024 -.384 -8.631 .001
Reliability .026 .033 .039 .802 .423
Customer service -.102 .026 -.200 -3.980 .001
Product compatibility .104 .037 .153 2.800 .005
Competitive price .081 .030 .138 2.693 .007
Source: Field Survey and Analysis of Data 2010 Level of significance (0.05%)
164
The R value (0.456) indicates the multiple correlation coefficients
between all the entered independent variables and dependent variables.
The R square value in the model summary table shows the portion of
the variance accounted for by the independent variable that is approximately
21 per cent of variance in satisfaction which is accounted for.
The ANOVA table indicates the p-level to be 0.001.this indicates that
the model is statistically significant at a confidence level of 99.999. The
P-level indicates the significance of the F- value.
Also note that t- tests significance of individual independent variables
indicates that Worthiness, responsiveness, warranty, usage experience, after
sale service, loyalty programs and repair are the independent variables which
are statistically significant in the model.
The standardized coefficients Beta column, gives the coefficients of
independent variables in the regression equation including all predictor
variables.
Y=.099X1-.124X2-.162X3+.224X4-.198X5+.037X6-.182X7+.317X8-.050X9-384X10+.039X11-
.200X12+.153X13+.138X14 (5.4)
5.4 FACTORS CONSIDERED FOR CUSTOMER LOYALTY
Loyalty factors should be developed over time, if the parameters for the
relationship are planned and implemented by the firm in a proper manner. As
the time period of relationship between a customer and business firm
increases, the profit accruing from such a customer towards the company also
makes a corresponding increase. The economic consequences of losing mature
customers and replacing them with new one are not the neutral processes.
5.4.1 Factors Considered for Loyalty White goods Audio Brands
The various factors considered for loyalty on durable white goods audio
brands are given in column 1 and rating scales are given in column 2 to 6. The
rank assigned the weighted mean score are in column 9.
165
Table 5.48
Loyalty Factors Considered on Various Audio Brands
Factors(1)
Stronglyagree
(2)
Agree(3)
Neutral(4)
Disagree(5)
Stronglydisagree
(6)
Totalscore
(7)
Mean(8)
Rank(9)
Deliver onpromises
200(23.5)
470(55.3)
120(14.1)
20(2.4)
40(4.7)
3320 3.86 5
Providesaccurate
brandinformation
210(24.4)
420(48.8)
150(17.4)
80(9.3)
0 3340 3.88 4
Value for me 190(22.1)
450(52.3)
170(19.8)
40(4.7)
10(1.2)
3350 3.89 3
Good brandchoice
180(20.9)
540(62.8)
90(10.5)
50(5.8)
0 3430 3.98 2
Handlescritical
problem well
150(17.4)
410(47.7)
200(23.3)
60(7.0)
40(4.7)
3150 3.66 9
Consistencein service
210(24.4)
380(44.2)
190(22.1)
30(3.5)
50(5.8)
3250 3.77 7
Lowest price 110(12.8)
450(52.3)
160(18.6)
90(10.5)
50(5.8)
3060 3.55 11
Lesstransaction
time
170
(19.8)
450(52.3)
140(16.3)
60(7.0)
40(4.7)
3230 3.75 8
Needsfulfillment
270(31.4)
400(46.5)
150(17.4)
10(1.2)
30(3.5)
3450 4.01 1
Rewardsprograms
240(27.9)
370(43.0)
140(16.3)
70(8.1)
40(4.7)
3280 3.81 6
Properlysettled
complaints
170
(19.8)
390(45.3)
140(16.3)
80(9.3)
80(9.3)
3070 3.56 10
Mean 3.79
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
166
Table 5.48 indicates the level of loyalty as expressed by audio brand
respondents towards their respective brand. In this table various factors
determining loyalty in audio brands are ranked in descending order given in
column 9. It is understood that the audio brands fulfill the needs of
respondents for the selection of their brands. The audio also scored well on
offering better product choice. As it stands, nature of consumer durable white
goods are being different, providing variety is difficult for this product. The
audio are rated high on making the respondents feel important (valuing their
respective customers). The audio provides accurate brand information to
respondents for the selection of consumer durable white goods. The
companies are found to deliver the service in tune with the promises made to
its valuable customers. Apparently audio brands did not do too well on reward
programs, consistency in service, time taken for each transaction and handles
critical problem for all respondents which are properly settled complaints.
Finally, audio brands do not deliver goods at lowest price.
Clearly, audio brands have scored well on the items that ‘needs
fulfillments’,’ good brand choice’, ‘value’,’ provide accurate brand
information’, and ‘deliver on promises’.
5.4.1.1Various Loyalty Parameters Considered Audio Brands
Table 5.49 shows certain parameters assigned for determining the
weighted score of audio brands which are given in the column 1 and selective
brands of audio are given in column 2 to 6 such as Sony, Creative, Samsung
LG and Philips.
167
Table 5.49
Loyalty- Audio Brands-Weighed Mean Score
BrandsParameters(1)
Sony(2)
Creative(3)
Samsung(4)
LG(5)
Philips(6)
Understand needs(P1) 3.78 4.15 3.85 4.14 4.25
Good brand choice(P2) 3.96 4.00 3.50 4.14 4.06
Value for me(P3) 3.14 4.00 4.00 4.71 3.81
Provide accurate brandinformation(P4)
3.64 4.23 4.00 4.14 3.87
Deliver on promises(P5) 3.82 4.00 4.00 4.14 3.93
Reward programs(P6) 3.42 4.00 4.00 4.28 4.00
Table 5.49 indicates that customers are highly loyal to the firm by
fulfilling needs of audio brands rated high for the brand of Philips. In terms of
good brand choice, value, promise on delivery and reward programs is more in
LG. Highly loyal to customer in providing accurate brand information by
creative.
Table 5.49-1
BrandsParameters
Sony Creative Samsung LG Philips
Understand needs �
Good brand choice �
Value for me �
Provide accurate brand information �
Deliver on promises �
Reward programs �
168
Figure 5.14
Loyalty Parameters with Respect to Selective Audio Brands
5.4.2 Factors Considered for Loyalty Washing Machine Brands
The various factors considered for loyalty white goods washing
machine brands are given in column 1 and rating scales are given in columns 2
to 6. The rank assigned on the weighted score is given in column 9.
Table 5.50
LOYALTY FACTORS CONSIDERED ON VARIOUS WASHING
MACHINE BRANDS
Factors(1)
Stronglyagree
(2)
Agree(3)
Neutral(4)
Disagree(5)
Stronglydisagree
(6)
Totalscore Mean Rank
Deliver onpromises
380(41.3)
380(41.3)
90(9.8)
40(4.3)
20(2.2)
3840 4.21 2
Providesaccurate
brandinformation
300(33.0)
460(50.5)
100(11.0)
40(4.4)
10(1.1)
3730 4.09 4
Value for me 290(31.9)
470(51.6)
110(12.1)
40(4.4)
0 3740 4.10 3
169
Table 5.50 Continue
Good brandchoice
410(45.1)
330(36.3)
150(16.5)
20(2.2)
0 3860 4.24 1
Handlescritical
problem well
250(27.5)
410(45.1)
150(16.5)
70(7.7)
30(3.3)
3510 3.85 8
Consistencein service
260(28.6)
440(48.4)
100(11.0)
60(6.6)
50(5.5)
3530 3.87 6
Lowest price 180(19.8)
410(45.1)
220(24.2)
50(5.5)
50(5.5)
3350 3.68 10
Lesstransaction
time
240(26.4)
430(47.3)
150(16.5)
70(7.7)
20(2.2)
3530 3.87 6
Needsfulfillment
270(29.7)
470(51.6)
110(12.1)
40(4.4)
20(2.2)
3660 4.02 5
Rewardsprograms
220(24.2)
410(45.1)
120(13.2)
110(12.1)
50(5.5)
3370 3.70 9
Properlysettled
complaints
210(23.1)
390(42.9)
150(16.5)
110(12.1)
50(5.5)
3330 3.65 11
Mean 3.93
Source: Field Survey and Analysis of Data 2010
Values within brackets show percentage
Table 5.50 expresses the ranking of responses of washing machine
brands respondents on various criteria’s of loyalty. In this table various factors
determining loyalty washing machine are ranked in descending order of their
loyalty. It is evident that washing machine brands have been given good brand
choice while selecting the brands by the respondents is given the first position.
Secondly it has been successful in delivering the goods as promised to its
customers. Third the company has provided personalized service to its
customers. It has also delivered correct product information to its customers,
who, by and large, would not have had much idea about the white goods
products or their differentiation. Fifthly, the company has understood the
170
needs of customers, but white goods washing machine seem to have slackened
on’ service consistency’, ‘less in traction time’, ‘handles critical problem ‘and’
rewards programs’.
5.4.2.1 Various Parameters Considered on White Goods –Loyalty-
Washing machine Brands.
Table 5.51 shows various parameters assigned for determining the
weighted score of washing machine brands which are given in column 1 and
selective brands of washing machine are given in columns 2 to 6 such as
Whirlpool, LG, IFB, Samsung and Videocon.
Table 5.51WASHING MACHINE BRANDS-LOYALTY-WEIGHTED MEAN SCORE
Brands
Parameters(1)
Whirlpool
(2)
LG
(3)
IFB
(4)
Samsung
(5)
Videocon
(6)
Good brand choice (P1) 3.90 4.11 4.33 3.72 4.50
Deliver on promises(P2) 4.37 4.55 4.20 3.95 4.25
Value for me( P3 ) 4.34 4.33 4.00 3.86 4.00
Provide accurate brandinformation (P4)
4.15 4.44 4.20 3.72 4.50
Need fulfillment (P5) 4.28 4.44 4.40 3.77 3.75
Consistence in service (P6) 3.81 3.55 3.80 3.45 3.25
Table 5.51 indicates that most of the customers are highly loyal in providing good
brand choice and providing accurate brand information to the customer’s by
Videocon. In terms of deliver promises and need fulfillment stands first by LG.
Whirlpool provides consistence service and value.
171
Table 5-51-1
Brands
Parameters
Whirlpool LG IFB Samsung Videocon
Good brand choice �
Deliver on promises �
Value for me �
Provide accurate brandinformation
�
Need fulfillment �
Consistence in service �
Figure 5.15
Loyalty parameters with respect to Selective Brands of washing machine
172
5.4.3 Loyalty Factors considered for Air conditioner Brands
Table 5.52 shows various factors considered on the loyalty for air
conditioner brands and are given in column 1 and rating scales are given in
columns 2 to 6.
Table 5.52
Loyalty Factors on Various Air conditioner Brands
Factors(1)
Stronglyagree
(2)
Agree(3)
Neutral(4)
Disagree(5)
Stronglydisagree
(6)
Totalscore mean Rank
Deliver onpromises
330(40.7)
320(39.5)
80(9.9)
50(6.2)
30(3.7)
3300 4.07 1
Providesaccuratebrandinformation
210(25.9)
390(48.1)
110(13.6)
70(8.6)
30(2.9)
3110 3.83 7
Value for me 190(23.5)
400(49.4)
160(19.8)
50(6.2)
10(1.2)
3140 3.87 4
Good brandchoice
330(40.7)
310(38.3)
100(12.3)
40(4.9)
30(3.7)
3300 4.07 1
Handlescriticalproblem well
160(19.8)
420(40.0)
120(14.8)
60(7.4)
50(6.2)
3010 3.71 11
Consistencein service
170(21.0)
460(56.8)
90(11.1)
30(3.7)
60(7.4)
3080 3.80 8
Lowest price 200(24.7)
400(49.4)
140(17.3)
30(3.7)
40(4.9)
3120 3.85 5
Lesstransactiontime
230(28.4)
390(48.1)
120(14.8)
30(2.9)
40(4.9)
3170 3.91 3
Needfulfillment
220(27.2)
370(45.7)
130(16.0)
60(7.4)
30(3.7)
3120 3.85 5
Rewardsprograms
250(30.9)
320(39.5)
100(12.3)
70(8.6)
70(8.6)
3040 3.75 10
Properlysettledcomplaints
260(32.1)
270(33.3)
160(19.8)
80(9.9)
40(4.9)
3060 3.77 9
Mean 3.86
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
173
Table 5.52 indicates the level of loyalty expressed by air conditioner
brand respondents towards their respective brands. The table shows various
factors considered for loyalty in air conditioner brands and are ranked in the
descending order as are given in column 9. It is to be understood that the air
conditioner brands scored well on offering better product choice to the
customers. The companies are found to deliver the service in tune with the
promises made to its customers. The time taken for each transaction to
customers is found satisfactory. Air conditioner brands are also rated high on
making the customers feel important (valuing the respective customers).
Companies also do well on delivering the air conditioner brands at lowest
price. Finally handling the critical problems is found not satisfactory.
5.4.3.1Various Parameters Considered on the White goods –Loyalty-Air
conditioner Brands.
Table 5.53 shows various parameters assigned for considering the
weighted score of air conditioner brands which given in column 1 and
selective brands of air conditioner are shown in columns 2 to 6 such as
Samsung, LG, Voltas, General and Carrier.
Table 5.53
Air conditioner Brands-Loyalty-Weighted mean score
BrandsParameters (1)
Samsung(2)
LG(3)
Voltas(4)
General(5)
Carrier(6)
Good brand choice(P1) 4.00 4.21 4.14 4.20 3.66Deliver on promises(P2) 3.90 4.06 3.92 4.80 4.33Less transactiontime(P3)
3.80 4.00 3.5 4.00 4.00
Value for me(P4) 3.70 3.96 3.85 3.60 4.00Lowest price(P5) 3.20 3.90 3.71 4.00 4.00Need fulfillment(P6) 4.10 3.78 3.50 3.60 4.33
Table 5.53 indicates that the customers are highly loyal LG by
providing good brand choice and less transaction time. Delivery promises, less
174
transaction time and price is the parameters bring the customers loyal to
General. Carrier stands first in loyal of less transaction time, value, price and
fulfillment of need.
Table 5.53-1
BrandsParameters
Samsung LG Voltas General Carrier
Good brand choice �
Deliver on promises �
Less transaction time � � �
Value for me �
Lowest price � �
Need fulfillment �
Figure 5.16
Loyalty Parameters with respect to Selective brands
Air Conditioner
175
5.4.4 Loyalty factors considered for Refrigerator Brands
Table 5.54 shows various factors considered on loyalty for refrigerator
brands as given in column 1 and rating scales are given in columns 2 to 6.
Table 5.54
LOYALTY FACTORS CONSIDERED ON VARIOUS
REFRIGERATOR BRANDS
Factors(1)
Stronglyagree
(2)Agree
(3)Neutral
(4)
Disagree(5)
Stronglydisagree
(6)
Totalscore Mean Rank
Deliver onpromises
410(43.2)
39.(41.1)
90(9.5)
40(4.2)
20(2.1)
3980 4.18 1
Providesaccuratebrandinformation
330(34.7)
480(50.5)
60(6.3)
70(7.4)
10(1.1)
3900 4.10 2
Value for me 290(30.5)
500(52.6)
80(8.4)
70(7.4)
10(1.1)
3840 4.04 4
Good brandchoice
370(38.9)
380(40.0)
130(13.7)
60(6.3)
10(1.1)
3890 4.09 3
Handlescriticalproblem well
200(21.1)
500(52.6)
190(20.0)
40(4.2)
20(2.1)
3670 3.86 9
Consistencein service
280(29.5)
430(45.3)
140(14.7)
80(8.4)
20(2.1)
3720 3.91 7
Lowest price 310(32.6)
380(40.0)
160(16.8)
60(6.3)
40(4.2)
3710 3.90 8
Lesstransactiontime
310(32.6)
430(45.3)
150(15.8)
40(4.2)
20(2.1)
3820 4.02 5
Needfulfillment
210(22.1)
560(58.9)
140(14.7)
30(3.2)
10(1.1)
3780 3.97 6
Rewardsprograms
210(22.1)
470(49.5)
120(12.6)
80(8.4)
70(7.4)
3520 3.70 11
Properlysettledcomplaints
230(24.2)
470(49.5)
150(15.8)
60(6.3)
40(4.2)
3640 3.83 10
Mean 3.96
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
176
Table 5.54 shows the ranking of responses to refrigerator brands
respondents on the various criteria’s of loyalty. It is evident that the
refrigerator brands have been successful in delivering promises made to its
customers. This factor is given the first position. Secondly it also provides
accurate brand information to its customers, who by and large, would not have
mach idea about white goods –refrigerator or their differentiation. Refrigerator
companies have seen that they are able to offer good brand choices to the
customers. The companies are rated high on making the customers feels
important (valuing their respective customers). The refrigerator companies
took comparatively less transaction time to complete the process. The
company has been providing personalized service to needs of customers. But
at the same time refrigerator companies seem to have blackened on ‘service
consistency’, ‘lowest price’, ‘handles critical problem’, ‘properly settled
complaints’ and ‘reward programs’.
It is understand that refrigerator companies are rated high on
relationship factors. To be more specific, the factors rated high are ‘deliver on
promise’, provide accurate brand information’ and ‘value ’. The first two
being relationship drivers, this means refrigerator brands should pay more
attention to’ rewards programs’.
5.4.4.1Various parameters considered on loyalty-Refrigerator Brands
Table 5.55 shows various parameters assigned for considering the
weighted score of refrigerator brands as given in column 1 and selective
brands of refrigerator are shown in columns 2 to 6 such as Godrej, Kelvinator,
Whirlpool, LG and Samsung.
177
Table 5.55
Refrigerator Brands-Loyalty-Weighted Mean score
BrandsParameters(1)
Godrej(2)
Kelvinator(3)
Whirlpool(4)
LG(5)
Samsung(6)
Deliver on promises(P1)
4.22 4.5 4.35 4.00 4.00
Provides accurate brandinformation(P2)
4.33 3.83 4.07 4.25 4.07
Good brand choice (P3) 4.27 3.66 4.25 3.87 3.92
Value for me (P4) 4.11 4.50 4.17 4.00 3.78
Less transactiontime(P5)
4.22 4.50 3.96 4.12 3.85
Need fulfillment(P6) 4.00 3.83 4.07 3.87 4.07
Table 5.55 indicates that the customers are highly loyal to promise on
delivery, value and less transaction time in Kelvinator. Providing accurate
brand information and good brand choice are more loyal to Godrej. Whirlpool
and Samsung fulfills the needs of the customer.
Table 5.55-1
BrandsParameters
Godrej Kelvinator Whirlpool LG Samsung
Deliver on promises �
Provides accurate brandinformation
�
Good brand choice �
Value for me �
Less transaction time �
Need fulfillment � �
178
Figure 5.17
Loyalty Parameters with Respect to Selective Refrigerator Brands
5.4.5 CUSTOMER LOYALTY– FACTOR ANALYSIS-AUDIO
BRANDS
Table 5.56- depicts the distribution of customer loyalty on various
criteria’s of audio brands. The criteria is to deliver on promises, provides
accurate brand information, value for me, good brand choice, handles critical
problem well, consistence in service, lowest price, less transaction time, need
fulfillment, rewards programs and properly settled complaints
Table 5.56
Factor analysis-Loyalty-Audio Brands
KMO and Bartlett's test
Kaiser-Meyer-Olkin measure of sampling adequacy. .827
Bartlett's test of sphericity Approx. Chi-square 4375.613
Df 55
Sig. .001
Total Variance Explained by Initial Eigen Values
179
Table 5.57
ComponentInitial eigen values
Total Percentage of variance Cumulative percentage
1 5.092 46.287 46.287
2 1.256 11.418 57.704
Extraction method: Principal component analysis.
Table 5.58
Component matrix ( Without rotation)
Criteria 1 2
Deliver on promises .555 -.002
Provides accurate brand information .806 -.021
Value for me .686 -.350
Good brand choice .580 -.627
Handles critical problem well .777 -.064
Consistence in service .585 .303
Lowest price .554 .644
Less transaction time .663 .261
Need fulfillment .674 -.292
Rewards programs .787 -.053
Properly settled complaints .748 .272
Varimax Rotated Factor Loading Matrix
180
Table 5.59
AttributesFactor loadings
Communalities(h2)F1 F2
Deliver on promises .400 .308
Provides accurate brand information .593 .649
Value for me .735 .593
Good brand choice .853 .730
Handles critical problem well .602 .608
Need fulfillment .687 .540
Rewards programs .601 .621
Consistence in service .625 .435
Lowest price .848 .722
Less transaction time .649 .508
Properly settled complaints .716 .633
Eigen values 3.229 3.118
Percentage of variance explained 29.358 28.346
Percentage of cumulative variance explained 29.358 57.704
Source: Field Survey and Analysis of Data 2010
KMO is calculated using correlation and partial correlation to test
whether the variables in our sample are adequate to correlate. A general rule of
thumb is that KMO value should greater than 0.5 for a loyalty factor analysis
to proceed, by observing the above results from the table 5.56 KMO value is
0.827; therefore we can proceed with factor analysis.
Bartlett’s test of sphericity is to find out the relationship between the
variables. A p- value < 0.05 indicates that it makes sense to continue with the
factor analysis, we found that P-value is < 0.001, therefore it is concluded that
there are relationship between our variables.
181
As evident from table 5.57, we find that 2 factors extracted together
account for 57.7 per cent of total variance. Hence we have reduced the number
of variables from 14 to 2 underlying factors.
From table 5.59, variable good brands choice loaded as (0.853), value
for me (0.735) and need fulfillments (0.687) on factor 1. Thus factor 1 can be
named as ‘brand equity’.
As for factor 2, it is evident that lowest price has the highest load of
0.848, properly settled complaints (0.716) and less transaction time be loaded
as 0.649, this factor can be termed as ‘price attributes’.
5.4.6 CUSTOMER LOYALTY– FACTOR ANALYSIS-WASHING
MACHINE BRANDS
Table 5.60 depicts the distribution of customer loyalty on various
criteria’s of washing machine brands. The criteria’s are to deliver the
promises, provide accurate brand information, value for me, good brand
choice, handles critical problem well, consistence in service, lowest price, less
transaction time, need fulfillment, rewards programs and properly settled
complaints
Factor analysis-Loyalty-Washing machine Brands
Table 5.60
KMO and Bartlett's test
Kaiser-Meyer-Olkin measure of sampling adequacy. .875
Bartlett's test of sphericity Approx. Chi-square 5686.671
df 55
Sig. .001
Total Variance Explained by Initial Eigen Values
182
Table 5.61
ComponentInitial eigen values
Total percentage of variance Cumulative percentage
1 5.728 52.076 52.076
2 1.150 10.455 62.531
Extraction method: Principal component analysis.
Table 5.62
Component matrix ( Without rotation)
Attributes 1 2
Deliver on promises .638 .526
Provides accurate brand information .761 .131
Value for me .727 -.004
Good brand choice .558 .646
Handles critical problem well .798 -.007
Consistence in service .637 -.210
Lowest price .592 -.301
Less transaction time .665 -.419
Need fulfillment .800 -.346
Rewards programs .855 .001
Properly settled complaints .834 .094
183
Varimax Rotated Factor Loading Matrix
Table 5.63
AttributesFactor loadings
Communalities(h2)F1 F2Value for me .583 .529
Handles critical problem well .642 .638
Consistence in service .635 .449
Lowest price .654 .441
Less transaction time .784 .618
Need fulfillment .847 .760
Rewards programs .682 .730
Properly settled complaints .609 .704
Deliver on promises .804 .684
Provides accurate brand information .562 .596
Good brand choice .852 .729
Eigen values 4.073 2.805
Percentage of variance explained 37.032 25.499
Percentage of cumulative varianceexplained
37.032 62.531
Source: Field Survey and Analysis of Data 2010
KMO is calculated using correlation and partial correlation to test
whether the variables in our sample are adequate to correlate. A general rule of
thumb is that KMO value should greater than 0.5 for a loyalty factor analysis
to proceed, by observing the above results from the table 5.60 KMO value is
0.875; therefore we can proceed with factor analysis.
Bartlett’s test of sphericity is to find out the relationship between the
variables. A p- value < 0.05 indicates that it makes sense to continue with the
factor analysis, we found that P is < 0.001, therefore it is concluded that there
are relationships between our variables.
184
As evident from table 5.61, we find that 2 factors extracted together
account for 62.53 per cent of total variance. Hence we have reduced the
number of variables from 14 to 2 underlying factors.
From table 5.63, variables needs fulfillment loaded as (0.847), less
traction time (0.784), and reward programs (0.682) on factor 1. Thus factor 1
can be named as ‘need fulfillments’.
As for factor 2, it is evident that good brand choice has the highest load
of 0.852, deliver on promises (0.804) be loaded as, this factor can be termed as
‘brand promises’.
5.4.7 CUSTOMER LOYALTY– FACTOR ANALYSIS- AIR
CONDITIONER BRANDS
Table 5.64 -5.67 depicts the distribution of loyalty factors of durable
white goods air conditioner brands. The criteria’s are to deliver the promises,
provides accurate brand information, value for me, good brand choice, handles
critical problem well, consistence in service, lowest price, less transaction
time, need fulfillment, rewards programs and properly settled complaints.
Factor Analysis-Loyalty-Air conditioner Brands
Table 5.64
KMO and Bartlett's test
Kaiser-Meyer-Olkin measure of sampling adequacy. .876
Bartlett's test of sphericity Approx. Chi-square 5375.20
df 55
Sig. .001
Total Variance Explained by Initial Eigen Values
185
Table 5.65
Component
Initial eigen values
Total Percentage ofvariance
Cumulativepercentage
1 5.814 52.858 52.858
2 1.196 10.869 63.728
Extraction method: Principal component analysis.
Table 5.66
Component matrix ( Without rotation)
1 2
Deliver on promises .511 -.615
Provides accurate brand information .846 -.130
Value for me .797 -.064
Good brand choice .121 .852
Handles critical problem well .772 .085
Consistence in service .721 .030
Lowest price .708 -.028
Less transaction time .688 .205
Need fulfillment .806 .123
Rewards programs .882 .074
Properly settled complaints .817 -.001
Varimax Rotated Factor Loading Matrix
186
Table 5.67
Criteria
Factor Loadings
Communalities(h2)F1 F2
Provides accurate brand information .829 .733
Value for me .787 .640
Handles critical problem well .777 .603
Consistence in service .720 .521
Lowest price .701 .502
Less transaction time .705 .515
Need fulfillment .814 .665
Rewards programs .885 .784
Properly settled complaints .813 .668
Deliver on promises .663 .639
Good brand choice 706 .740
Eigen values 4.073 2.805
Percentage of variance explained 37.032 25.499
Percentage of cumulative varianceexplained 37.032 62.531
KMO is calculated using correlation and partial correlation to test
whether the variables in our sample are adequate to correlate. A general rule of
thumb is that KMO value should be greater than 0.5 for a loyalty factor
analysis to proceed, by observing the above results from table 5.64 KMO
value is 0.876; therefore we can proceed with factor analysis.
Bartlett’s test of sphericity is to find out the relationship between the
variables. A p- value < 0.05 indicates that it makes sense to continue with the
factor analysis, we found that P is < 0.001, therefore it is concluded that there
are relationships between our variables.
187
As evident from table 5.65, we find that 2 factors extracted together
account for 64 per cent of total variance. Hence we have reduced the number
of variables from 14 to 2 underlying factors.
From table 5.67, variables reward programs loaded as (0.885), provide
accurate brand information (0.829), need fulfillment (0.814), properly settled
complaints (0.813), handles critical problem well (0.777) on factor 1. Thus
factor 1 can be named as ‘pre sale attributes’.
As for factor 2, it is evident that good brand choice is the highest load
of 0.706, deliver on promises’ (0.663), this factor can be termed as ‘brand
value’.
5.4.8 CUSTOMER LOYALTY– FACTOR ANALYSIS-
REFRIGERATOR BRANDS.
Table 5.68-5.71 depicts the distribution of loyalty factors on
refrigerator brands. The criteria is to deliver promises, provides accurate brand
information, value for me, good brand choice, handles critical problem well,
consistence in service, lowest price, less transaction time, need fulfillment ,
rewards programs and properly settled complaints.
Factor Analysis-Loyalty-Refrigerator Brands
Table 5.68
KMO and Bartlett's test
Kaiser-Meyer-Olkin measure of sampling adequacy. .862
Bartlett's test of Sphericity Approx. Chi-square 4328.116
df 55
Sig. .001
Total Variance Explained by Initial Eigen Values
188
Table 5. 69
ComponentInitial eigen values
Total Percentage of variance Cumulative percentage
1 5.061 46.007 46.007
2 1.030 9.366 55.373
3 1.006 9.147 64.520
Extraction method: Principal component analysis.
Table 5.70
component Matrix ( Without rotation)
AttributesComponent
1 2 3
Deliver on promises .571 .550 .392
Provides accurate brand information .730 .132 -.294
Value for me .685 .352 -.160
Good brand choice .605 .294 -.237
Handles critical problem well .701 -.203 -.297
Consistence in service .614 .050 .243
Lowest price .527 -.387 .612
Less transaction time .657 -.526 -.155
Need fulfillment .742 -.120 -.216
Rewards programs .814 -.121 .015
Properly settled complaints .759 .028 .303
Varimax Rotated Factor Loading Matrix
189
Table 5.71
CriteriaFactor Loadings
CommunalitiesF1 F2 F3Less transaction time .780 .733
Need fulfillment .677 .612
Rewards programs .595 .678
Provides accurate brand information .592 .637
Handles critical problem well .735 . .620
Deliver on promises .778 .781
Value for me .685 .619
Good brand choice .591 .508
Consistence in service .468 .438
Lowest price . .876 .803
Properly settled complaints .592 .668
Eigen values 2.830 2.388 1.880
Percentage of variance explained 25.725 21.707 17.089
Percentage of cumulative variance
explained25.725 47.432 64.520
KMO is calculated using correlation and partial correlation to test
whether the variables in our sample are adequate to correlate. A general rule of
thumb is that KMO value should be greater than 0.5 for a loyalty factor
analysis to proceed, by observing the above results from table 5.68 KMO
value is 0.862; therefore we can proceed with factor analysis.
Bartlett’s test of sphericity is to find out the relationship between the
variables. A p- value < 0.05 indicates that it makes sense to continue with the
factor analysis, we found that p value is < 0.001, therefore it is concluded that
there are relationships between our variables.
190
As evident from table 5.69, we find that 3 factors extracted together
account for 65 per cent of total variance. Hence we have reduced the number
of variables from 14 to 3 underlying factors.
From table 5.71, variables less transaction time loaded as (0.780),
handles critical problem well (0.735), and need fulfillment (0.677) on factor 1.
Thus factor 1 can be named as ‘process attributes’.
As for factor 2, it is evident that delivering promises has the highest
load of 0.778, value for me be loaded as 0.685, this factor can be termed as
‘delivering attributes’.
It is evident that from the table that lowest price has the highest load of
0.876, hence this factor can be interpreted as ‘price attributes’.
5.4.9 REGRESSION MODEL ON CUSTOMER LOYALTY
An in depth study of loyalty would not be complete without the
identification of the key indicators of customer loyalty.
Assuming the existence of linear relationship between the independent
variables and dependent variable, multiple regression analysis has done
between the level customer loyalty of the different predictor variables of
loyalty and overall loyalty of the service.
5.4.9.1 Regression Model on Loyalty Audio Brands.
This study attempted to develop a model to analyze loyalty of audio
brand. Enter method regression analysis of loyalty (Y) is performed with the
variables X1- deliver on promises; X2-provides accurate brand information ,
X3- value for me; X4- good brand choice; X5-handles critical problem well;
X6- consistence in service;X7- lowest price;X8- Less transaction time; X9-need
fulfillment;X10- rewards programs,X11- properly settled complaints for the
audio brand.
191
Table 5.72
Regression Model-Customer Loyalty-Audio Brands
Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .776a .602 .596 .227
ANOVAb
Model Sum of Squares df Mean Square F Sig.1 Regression 65.335 11 5.940 114.994 .001a
Residual 43.283 838 .052Total 108.618 849
Coefficientsa
ModelUn standardized
CoefficientsStandardizedCoefficients t Sig.
B Std. Error Beta(Constant) 2.799 .055 51.149 .000Deliver on promises -.054 .010 -.143 -5.250 .001Provides accurate brandinformation -.065 .014 -.159 -4.480 .001
Value for me -.017 .013 -.040 -1.335 .182Good brand choice -.108 .015 -.222 -7.298 .001Handles critical problemwell -.031 .012 -.085 -2.643 .008
Consistence in service -.011 .010 -.033 -1.118 .264Lowest price .028 .011 .081 2.639 .008Less transaction time -.085 .012 -.239 -7.395 .001Need fulfillment -.036 .012 -.093 -3.132 .002Rewards programs -.048 .012 -.146 -4.075 .001
Properly settled complaints .004 .010 .014 .408 .683a. Dependent Variable: overall audio loyalty
Source: Field Survey and Analysis of Data 2010. Level of significance (0.05%)
The R value (0.776) indicates the multiple correlation coefficients
between all the entered independent variables and dependent variables.
192
The R square value in the model summary table shows the portion of
the variance accounted for by the independent variables that is approximately
60 percent of variance in loyalty is accounted for by.
The ANOVA table indicates the p-level to be 0.001.This indicates that
the model is statistically significant at a confidence level of 99.999. The
P-level indicates the significance of the F value.
Also note that t- tests significance of individual independent variables
indicate that deliver on promises, provides accurate brand information, good
brand choice, handles critical problem well, lowest price, less transaction time,
need fulfillment, rewards programs for the audio brands are the independent
variables which are statistically significant in the model.
The standardized coefficients Beta column, gives the coefficients of
independent variables in the regression equation including all the predictor
variables.
Loyalty Y = -0.143X1-0.159X2 -0.040X3 -0.222X4 -0.085X5 -0.033X6 +0.081X7 -
0.239X8 -.093 X9 -0.146X10 +0.014X11 (5.5)
5.4.9.2 Regression Model on Customer Loyalty Washing machine Brand.
This study attempted to develop a model to analyze loyalty of washing
machine brands. Enter method regression analysis of loyalty (Y) is performed
with the variables X1- deliver on promises; X2- provides accurate brand
information , X3-value for me; X4- good brand choice; X5- handles critical
problem well; X6- consistence in service;X7- lowest price;X8- less transaction
time; X9-need fulfillment;X10- rewards programs,X11- properly settled
complaints for the washing machine brands.
193
Table 5.73
Regression Model-Loyalty-Washing machine Brands
Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .842a .710 .706 .206
ANOVAb
ModelSum of
Squaresdf Mean Square F Sig.
1 Regression 93.595 11 8.509 199.637 .000a
Residual 38.273 898 .043
Total 131.868 909
Coefficientsa
ModelUnstandardized
CoefficientsStandardizedCoefficients t Sig.
B Std. Error Beta
(Constant) 3.141 .054 57.991 .000
Deliver on promises -.042 .011 -.103 -3.963 .001
Provides accurate brandinformation
-.181 .012 -.400 -14.588 .001
Value for me -.066 .013 -.134 -5.031 .001
Good brand choice -.039 .012 -.081 -3.306 .001
Handles critical problem well .020 .011 .054 1.824 .069
Consistence in service -.036 .008 -.101 -4.386 .001
Lowest price -.014 .008 -.037 -1.662 .097
Less transaction time -.070 .010 -.177 -6.752 .001
Need fulfillment -.018 .014 -.041 -1.297 .195
Rewards programs -.033 .012 -.097 -2.759 .006
Properly settled complaints -.009 .011 -.027 -.841 .401
a. Dependent Variable: overall washing machine loyalty
Source: Field Survey and Analysis of Data 2010. Level of significance (0.05%)
194
The R value (0.842) indicates the multiple correlation coefficients
between all the entered independent variables and dependent variables.
The R square value in the model summary table shows the portion of
the variance accounted for by the independent variables that is approximately
71 percent of variance in loyalty is accounted for by.
The ANOVA table indicates the p-level to be 0.001.This indicates that
the model is statistically significant at a confidence level of 99.999. The P-
level indicates the significance of the F value.
Also note that t- tests significance of individual independent variables
indicates that delivery on promises, provides accurate brand information,
value for me, good brand choice, consistence in service, less transaction time,
rewards programs, properly settled complaints are the independent variables
which are statistically significant in the model.
The standardized coefficients Beta column, gives the coefficients of
independent variables in the regression equation including all the predictor
variables.
Loyalty Y = -0.103X1 -0.400X2 -0.134X3 -0.081X 4 +.054X5 -0.101X6 -0.037X7 -
0.177X 8 -0.041X9 -0.097 X10 -0.027 X11. (5.6)
5.4.9.3 Regression model on Customer Loyalty Air conditioner Brands.
This study attempted to develop a model to analyze loyalty of air
conditioner brands. Enter method regression analysis of loyalty (Y) is
performed with the variables X1-deliver on promises;X2-provides accurate
brand information;X3-value for me; X4- good brand choice; X5- handles
critical problem well; X6- consistence in service;X7- lowest price;X8-less
transaction time; X9-need fulfillment;X10- rewards programs;X11- properly
settled complaints for the air conditioner brands.
195
Table 5.74
Regression Model-Customer Loyalty-Air conditioner Brands
Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .865a .748 .745 .213
ANOVAb
Model Sum ofSquares df Mean Square F Sig.
1 Regression 107.297 11 9.754 215.344 .001a
Residual 36.146 798 .045
Total 143.443 809
Coefficientsa
Model
UnstandardizedCoefficients
StandardizedCoefficients t Sig.
B Std. Error Beta
(Constant) 2.706 .048 56.926 .001
Deliver on promises -.046 .009 -.115 -5.070 .001
Provides accurate brandinformation -.016 .014 -.040 -1.149 .251
Value for me -.017 .014 -.036 -1.199 .231
Good brand choice -.029 .003 -.158 -8.332 .001
Handles critical problem well .024 .011 .061 2.299 .022
Consistence in service -.076 .010 -.189 -7.683 .001
Lowest price .031 .011 .074 2.794 .005
Less transaction time -.009 .011 -.022 -.845 .399
Need fulfillment -.022 .012 -.054 -1.847 .065
Rewards programs -.212 .014 -.615 -15.648 .001
Properly settled complaints -.013 .012 -.036 -1.121 .263
a. Dependent Variable: overall ac loyalty
Source: Field Survey and Analysis of Data 2010. Level of significance (0.05%)
196
The R value (0.865) indicates the multiple correlation coefficients
between all the entered independent variables and dependent variables.
The R square value in the model summary table shows the portion of
the variance accounted for by the independent variables that is approximately
75 percent of variance in loyalty is accounted for by.
The ANOVA table indicates the p-level to be 0.001.This indicates that
the model is statistically significant at a confidence level of 99.999. The P-
level indicates the significance of the F value.
Also note that t- tests significance of individual independent variables
indicates that deliver on promises, good brand choice, consistence in service,
lowest price, rewards programs are the independent variables which are
statistically significant in the model.
The standardized coefficients Beta column, gives the coefficients of
independent variables in the regression equation including all the predictor
variables.
Loyalty Y = -0.115X1 -0.040X2 -0.036X3-0.158X4+0.061X 5-0.189X6+0.074X7-
0.022 X8 -0.054X9 -0.615 X10 -0.036 X11 ( 5.7 )
5.4.9.4 Regression model on Customer Loyalty Refrigerator Brands.
This study attempted to develop a model to analyze loyalty of audio
brands. Stepwise regression analysis of loyalty (Y) is performed with the
variables X1-deliver on promises; X2-provides accurate brand information ,
X3-value for me; X4-good brand choice; X5-handles critical problem well; X6-
consistence in service;X7-lowest price;X8- less transaction time; X9-need
fulfillment;X10-rewards programs;X11-properly settled complaints for the
refrigerator brands.
197
Table 5.75
Regression Model-Loyalty-Refrigerator Brands
Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .820a .673 .669 .192
ANOVAb
Model Sum of Squares df Mean Square F Sig.
1 Regression 71.369 11 6.488 175.262 .001a
Residual 34.724 938 .037
Total 106.094 949
Coefficientsa
ModelUnstandardized
CoefficientsStandardizedCoefficients t Sig.
B Std. Error Beta(Constant) 2.403 .046 52.091 .000
Deliver on promises -.091 .009 -.250 -10.593 .001
Provides accurate brandinformation -.009 .010 -.024 -.871 .384
Value for me -.038 .010 -.100 -3.959 .001
Good brand choice -.032 .008 -.089 -3.916 .001Handles critical problemwell -.092 .010 -.238 -9.196 .001
Consistence in service .062 .008 .182 7.767 .001
Lowest price .070 .007 .222 9.534 .001Less transaction time -.080 .009 -.220 -8.661 .001
Need fulfillment .041 .012 .094 3.470 .001
Rewards programs -.142 .009 -.477 -15.759 .001
Properly settledcomplaints -.014 .009 -.041 -1.481 .139
Source: Field Survey and Analysis of Data 2010.
Level of significance (0.05%)
198
The R value (0.820) indicates the multiple correlation coefficients
between all the entered independent variables and dependent variables.
The R square value in the model summary table shows the portion of
the variance accounted for by the independent variables that is approximately
67 percent of variance in loyalty is accounted for by.
The ANOVA table indicates the p-level to be 0.001.This indicates that
the model is statistically significant at a confidence level of 99.999. The P-
level indicates the significance of the F value.
Also note that t- tests significance of individual independent variables
indicates that deliver on promises, value for me, good brand choice, handles
critical problem well, consistence in service, lowest price, less transaction
time, need fulfillment, rewards programs are the independent variables are
statistically significant in the model.
The standardized coefficients Beta column, gives the coefficients of
independent variables in the regression equation including all the predictor
variables.
Loyalty Y = -0.250X1- 0.024X2 -0.100 X3 -0.089X4 -0.238X5 +0.182X6 +0.222 X7 -
0.220 X8 +0.094X9 -0.477X10 -0.041 X11. (5.8)
5.5 CUSTOMER RETENTION
The consumer durable white goods sector is analyzed using ten
independent variables relevant for retaining customers. Table 5.76, 5.78, 5.80,
5.82 gives the responses measured on likert’s scale.
5.5.1 Opinion on Customer Retention of Audio Brands
Table 5.76 shows various factors to retain the white goods audio brands
respondents and is given in column 1 and columns 2 to 6 are shown with the
rating scales.
199
Table 5.76
OPINION ON CUSTOMER RETENTION OF AUDIO BRANDS
Factors(1)
Stronglyagree
(2)
Agree(3)
Neutral(4)
Dis-agree
(5)
Stronglydisagree
(6)
Totalscore
Averagemean Rank
Eliminateserviceirritants
290(33.7)
320(37.2)
180(20.9)
40(4.7)
30(3.5) 3380 3.93 2
Provideloyaltybenefits
170(19.8)
460(53.5)
170(19.8)
40(4.7)
20(2.3) 3300 3.83 5
Assistcustomer inmakingbrand choice
220(25.6)
400(46.5)
160(18.6)
60(7.0)
20(2.3) 3320 3.86 3
Provideservicebeyondexpectations
210(24.4)
420(48.8)
130(15.1)
80(9.3)
20(2.3) 3300 3.83 5
Provide thebenefitsoffered bycompetitors
180(20.9)
440(51.2)
150(17.4)
30(3.5)
60(7.0) 3230 3.75 9
Satisfactorilysettled allservicerelatedproblems
190(22.1)
480(55.8)
80(9.3)
80(9.3)
30(3.5) 3300 3.83 5
Sellingvariousproductitems
160(18.6)
490(57.0)
140(16.3)
60(7.0)
10(1.2) 3310 3.84 4
Buildemotionalcommitmentin therelationship
200(23.3)
390(45.3)
180(20.9)
60(7.0)
30(3.5) 3250 3.77 8
Buildingcompanyimage
250(29.1)
410(47.7)
120(14.0)
70(8.1)
10(1.0) 3400 3.95 1
Maintainregularinteractionwithcustomers
160(18.6)
500(58.1)
60(7.0)
80(9.3)
60(7.0) 3200 3.72 10
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
200
Table 5.76 shows that respondents’ opinion on various factors is
necessary for retaining customers in audio brands. The main factors which
could help retain customers is found to be ’building company image’. Majority
(33.7 percent) of the respondent’s opinion that firm could be bound to
eliminate is the service irritants. This was followed by ‘assist customers in
making brand choice’, ‘selling various product items’, ‘provide loyalty
benefits’,’ provide service beyond expectations’ in that order,’ maintaining
regular interaction with the customer’, ‘satisfactorily settled all service related
problems respectively. Contrary to general belief,’ maintain regular interaction
with customers ‘are found to be not important for improving customer
retention. Similarly building emotional commitment in the relationship is also
not much relevant, but the customers are very keen on providing loyalty
benefits. Thus, it is to be believed audio companies could improve the
retention levels if they could ‘build company image’ to their customers.
5.5.1.1 Parameters considered for White Goods –Retention-Audio brands.
Table 5.77 shows certain parameters assigned for considering the
weighted score of audio brands which is given in column 1 and selective
brands of audio are given in columns 2 to 6 such as Sony, Creative, Samsung,
LG and Philips.
Table 5.77AUDIO BRANDS-RETENTION-WEIGHTED MEAN SCORE
BrandsParameters (1)
Sony(2)
Creative(3)
Samsung(4)
LG(5)
Philips(6)
Building company image (P1) 3.75 4.30 4.25 3.71 3.87
Eliminate service irritants(P2) 3.60 4.23 3.87 4.00 4.25
Assist customers making brandchoice(P3)
3.64 4.07 3.87 4.00 4.06
Selling various product items (P4) 3.67 4.00 3.85 4.57 3.75
Provide loyalty benefits(P5) 3.67 3.84 3.62 3.85 4.12
201
Table 5.77 clearly indicates that the customers retains in creative by
company image and assisting the customer making brands choice. The service
irritants eliminate and loyalty benefits that retains the customer by Philips.
Selling various products items retains by LG.
Table 5.77-1
Brands
Parameters
Sony Creative Samsung LG Philips
Building company image �
Eliminate service irritants �
Assist customer making brand choice �
Selling various product items �
Provide loyalty benefits �
Figure 5.18
Retention Parameters with Respect to Audio Brands
202
5.5.2 Opinion On Customer Retention Of Washing Machine Brands
Table 5.78 shows various factors considering the respondents in order
to retain the washing machine brands are given in column 1 and in columns 2
to 6 are given in rating scales.
Table 5.78
OPINION ON CUSTOMER RETENTION OF WASHING
MACHINE BRANDS
Factors(1)
Stronglyagree
(2)
Agree(3)
Neutral(4)
Disagree(5)
Stronglydisagree
(6)
Totalscore
Averagemean Rank
Eliminateserviceirritants
370(41.1)
250(27.8)
210(23.3)
30(3.3)
40(4.4) 3580 3.97 3
Provide loyaltybenefits
210(23.3)
460(51.1)
90(10.0)
140(15.6) 0 3440 3.82 10
Assistcustomers inmaking brandchoice
150(16.7)
600(66.7)
80(8.9)
50(5.6)
20(2.2) 3510 3.90 6
Provideservice beyondexpectations
170(18.9)
530(58.9)
120(13.3)
60(6.7)
20(2.2) 3470 3.85 8
Provide thebenefitsoffered bycompetitors
300(33.3)
410(45.6)
110(12.2)
70(7.8)
10(1.1) 3620 4.02 2
Satisfactorilysettled allservice relatedproblems
250(27.8)
430(47.8)
160(17.8)
50(5.6)
10(1.1) 3560 3.95 4
Selling variousproduct items
200(22.2)
490(54.4)
170(18.9)
20(2.2)
20(2.2) 3530 3.92 5
Buildemotionalcommitment intherelationship
260(28.9)
380(42.2) 140
(15.6)90
(8.6)30
(3.3) 3450 3.83 9
Buildingcompanyimage
250(27.8)
510(56.7)
90(10.0)
40(4.4)
10(1.1) 3650 4.05 1
Maintainregularinteractionwith customers
250(27.8)
460(51.1)
70(7.8)
80(8.9)
40(4.4) 3500 3.88 7
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
203
Table 5.78 shows respondents’ opinion on various factors necessary for
retaining the customers in washing machine brands. The main factors which
could help to retain customers are found to be’ building company image’.
Respondent’s opinion that provide the benefits are offered by competitors.
This is followed by ‘eliminating service irritants’, ‘satisfactorily settled all
service related problems’ selling various product items to the customers, assist
customers in making brand choice in that order. Contrary to general belief,
‘provide loyalty benefits ‘ ‘build emotional commitment in the relationship’,
‘provide service beyond expectations’ is found to be not important for
improving customer retention. Thus, it is to be believed that the washing
machine companies could improve the retention levels if they could’ build
company image’ to their customer.
5.5.2.1Various parameters considered for durable white goods –
Retention-Washing Machine brands.
Table 5.79 shows various parameters assigned for considering the
weighted mean score of washing machine brands given in column 1 and
selective brands of washing machine shown are given in columns 2 to 6 such
as Whirlpool, LG, IFB, Samsung and Videocon.
Table 5.79
Washing Machine Brands-Weighted Mean Score
BrandsParameters (1)
Whirlpool(2)
LG(3)
IFB(4)
Samsung(5)
Videocon(6)
Building company image (P1) 3.93 4.22 4.20 3.90 4.45
Provide the benefits offered bycompetitors(P2)
4.06 4.33 4.00 3.72 4.50
Eliminate service irritants (P3) 4.06 3.77 4.13 3.72 5.00
Satisfactorily settled all servicerelated problems (P4)
4.03 4.55 3.80 3.74 4.52
Selling various product items(P5) 3.83 4.22 4.00 4.09 3.50
204
Table 5.79 indicates that customers retains in Videocon by company
image, same benefits offered by competitors and eliminating the service
irritants. Settling all service related problems and selling various product items
retains the customer by LG.
Table 5.79-1
BrandsParameters
Whirlpool LG IFB Samsung Videocon
Building company image �
Provide the benefits offered bycompetitors
�
Eliminate service irritants �
Satisfactorily settled all servicerelated problems
�
Selling various products items �
Figure 5.19
Retention Parameters with Respect to Washing Machine Brands
205
5.5.3 OPINION ON CUSTOMER RETENTION AIR CONDITIONER
BRANDS
Table 5.80 shows various factors on the customers retaining the air
conditioner brands are given in column 1 and in columns 2 to 6 are given the
rating scales.
Table 5.80
OPINION ON CUSTOMER RETENTION AIR CONDITIONER BRANDS
Factors(1)
Stronglyagree
(2)
Agree(3)
Neutral(4)
Disagree(5)
Stronglydisagree
(6)
Totalscore
Averagemean Rank
Eliminateservice irritants
350(43.2)
260(32.1)
130(16.0)
30(3.7)
40(4.9) 3280 4.04 2
Provide loyaltybenefits
260(32.1)
350(43.2)
110(13.6)
40(4.9)
50(6.2)
3160 3.90 8
Assist customerin making brandchoice
210(25.9)
430(53.1)
90(11.1)
70(8.6)
10(1.2) 3190 3.93 5
Provide servicebeyondexpectations
170(21.0)
490(60.5)
80(9.9)
50(6.2)
20(5.2) 3170 3.91 7
Provide thebenefits offeredby competitors
230(28.4)
420(51.9)
100(12.3)
40(4.9)
20(2.5) 3230 3.98 4
Satisfactorilysettled allservice relatedproblems
280(34.6)
380(46.9)
70(8.6)
40(4.9)
40(4.9) 3250 4.01 3
Selling variousproduct items
190(23.5)
450(55.6)
100(12.3)
70(8.6) 0 3190 3.93 6
Build emotionalcommitment inthe relationship
250(30.9)
330(40.7)
120(14.8)
50(6.2) 60
(7.4) 3090 3.81 10
Buildingcompany image
270(33.3)
390(48.1)
90(11.1)
50(6.2)
10(1.1) 3290 4.06 1
Maintainregularinteraction withcustomer
190(23.5)
440(54.3)
70(8.6)
80(9.9)
30(3.7) 3110 3.83 9
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
206
In table 5.80, the respondent’s opinion on various factors is necessary
for retaining the customers for air conditioner brands. The main factor which
could help retain customers is found to be’ building company image’. Majority
of the respondents are in the opinion that ‘eliminate the service irritants,
‘satisfactorily settled all service related problems’ ‘assist respondents in
making brand choice’, ‘selling various product items to the customer’,
‘provide loyalty benefits ‘ in that order. Contrary to general belief provide the
benefits offered by competitors’ ,’build emotional commitment in the
relationship’ and ‘maintain regular interaction with customer’ is found to be
not important for improving customer retention. Thus, it is to be believed that
the air conditioner companies could improve the retention levels if they could’
build company image’ to their customers.
5.5.3.1 Parameters considered for white goods –Retention-Air conditioner
brands.
Table 5.81 shows various parameters assigned for considering the
weighted score of air conditioner brands which is given in column 1 and
selective brands of air conditioner are shown in columns 2 to 6 such as
Samsung, LG, Voltas, General and Carrier.
Air Conditioner Brands-Weighted Mean Score
Table 5.81
BrandsParameters (1)
Samsung(2)
LG(3)
Voltas(4)
General(5)
Carrier(6)
Building company image (P1) 3.90 3.96 4.57 3.60 4.33
Eliminate service irritants (P2) 3.90 4.06 4.71 4.60 3.33
Satisfactorily settled all servicerelated problems(P3)
4.10 3.72 4.21 4.20 4.66
Provide the benefits offered bycompetitors (P4)
4.00 3.84 4.21 4.20 4.33
Assist customers in making brandchoice(P5)
3.80 3.81 4.00 4.00 3.66
207
Table 5.81 clearly indicates that customers who retains by Voltas
building company image, eliminating the service irritants and assisting the
customers in making brand choice. The parameter of assisting customers in
making brand choice stands only to retain general. Carrier retains the customer
by solving all service related problems and providing the benefits offered by
competitors
Table 5.81-1
BrandsParameters
Samsung LG Voltas General Carrier
Building company image �
Eliminate service irritants �
Satisfactorily settled all servicerelated problems
�
Provide the benefits offered bycompetitors
�
Assist customer in making brandchoice
� �
Figure 5.20
Retention Parameters with Respect to Air Conditioner Brands
208
5.5.4 OPINION ON RETENTION OF REFRIGERATOR BRANDS
Table 5.82 shows various factors considering retention of customers to
white goods refrigerator brands which are given in column 1 and columns 2 to
6 shows the rating scales.
OPINION ON CUSTOMER RETENTION OF REFRIGERATORBRANDS
Table 5.82
Factors(1)
Stronglyagree
(2)
Agree(3)
Neutral(4)
Disagree(5)
Stronglydisagree
(6)
Totalscore
Averagemean Rank
Eliminateserviceirritants
440(46.3)
300(31.6)
110(11.6)
40(4.2)
60(6.3) 3780 3.97 6
Provideloyaltybenefits
270(28.4)
500(52.6)
80(8.4)
90(9.5)
10(1.1) 3720 3.91 7
Assistcustomer inmaking brandchoice
230(24.2)
490(51.6)
160(16.8)
60(6.3)
10(1.1) 3660 3.85 9
Provideservice beyondexpectations
260(27.4)
480(50.5)
50(5.3)
130(13.7)
30(3.2) 3870 4.07 3
Provide thebenefitsoffered bycompetitors
300(31.6)
490(51.6)
100(10.5)
50(5.3)
10(1.1) 3910 4.11 1
Satisfactorilysettled allservice relatedproblems
340(35.8)
430(45.3)
140(14.7)
30(3.2)
10(1.1) 3780 3.97 4
Selling variousproduct items
270(28.4)
470(49.5)
140(14.7)
60(6.3)
10(1.1) 3780 3.97 4
Buildemotionalcommitmentin therelationship
250(26.3)
420(44.2)
160(16.8)
60(6.3)
60(6.3) 3590 3.77 10
Buildingcompanyimage
340(35.8)
460(48.4)
90(9.5)
40(4.2)
20(2.1) 3910 4.11 1
Maintainregularinteractionwith customer
300(31.6)
440(46.3)
60(6.3)
90(9.5)
60(6.3) 3680 3.87 8
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
209
Table 5.82 shows respondents’ opinion on various factors necessary for
retaining customers in refrigerator brands. The main factor which could help
retain customers is found to be’ building company image’. Majority of
respondents are of the opinion that, provide the ‘benefits offered by
competitors, ‘provide service beyond their expectations’. This is followed by
‘satisfactorily settled service related problems,’ ‘selling various product items
to the customer,’ eliminate the service irritants’, ‘provide loyalty benefits’ in
that order. Contrary to general belief, ‘assist customers in making brand
choice’, ‘build emotional commitment in the relationship’ and ‘maintain
regular interaction with customer’ are found to be not important for improving
customer retention. Thus, it is to be believed that the refrigerator brands could
improve the retention levels if they could ‘build company image’ to their
customers.
5.5.4.1Parameters considered for the white goods –Retention-Refrigerator
Brands
Table 5.83 shows various parameters assigned for determining the
weighted score of refrigerator brands as given in column 1 and selective
brands of refrigerator are given in columns 2 to 6 which show Godrej,
Kelvinator, Whirlpool, LG and Samsung.
Table 5.83
Retention-Refrigerator brands-Weighted Mean Score
BrandsParameters (1)
Godrej(2)
Kelvinator(3)
Whirlpool(4)
LG(5)
Samsung(6)
Building company image (P1) 4.05 3.83 4.32 4.06 4.50Provide the benefits offered bythe competitors (P2)
4.33 4.5 4.00 4.06 4.07
Provide service beyondexpectations (P3)
3.94 4.16 3.64 3.93 4.35
Satisfactorily settled all servicerelated problems (P4)
4.27 4.5 4.17 4.12 3.92
Selling various product items(P5)
4.05 3.83 4.28 3.93 3.85
210
Table 5.83 clearly indicates that the customer retains in kelvinator by
providing same benefits and solving all service problems. Whirlpool retains
the customer by selling various product items. Samsung creates image and
service beyond expectations retains the customers.
Table 5.83-1
BrandsParameters
Godrej Kelvinator Whirlpool LG Samsung
Building company image �
Provide the benefits offeredby the competitors
�
Provide service beyondexpectations
�
Satisfactorily settled allservice related problems
�
Selling various product items �
Figure 5.21
Retention Parameters with Respect to Refrigerator Brands
211
5.5.1 POST PURCHASE BEHAVIOUR (CUSTOMER SWITCHING)
5.5.1.1Factor Considered While Switching over to other White Goods
Audio Brands
Table 5.84 shows various factors that are considered to switch over to
other white goods audio brands as given in column 1 and columns 2 to 6 show
rating scales.
REASONS FOR SWITCHING AMONG THE AUDIO BRANDS
Table 5.84
Factors(1)
Stronglyagree
(2)
Agree(3)
Neutral(4)
Disagree(5)
Stronglydisagree
(6)
Totalscore
Averagemean Rank
Unsettledcustomercomplaints
280(32.6)
330(38.4)
120(14.0)
40(4.7)
90(10.5)
3250 3.77 7
Undesirablestaff attitudes
170(19.8)
380(44.2)
160(18.6)
110(12.8)
40(4.7)
3110 3.61 11
Not making thecustomer feelvalued
190(22.1)
440(51.2)
130(15.1)
60(7.0)
40(4.7)
3260 3.79 5
Poorrespondentsservice
210(24.4)
450(52.3)
80(9.3)
50(5.8)
70(8.1)
3260 3.79 5
Locationchange
220(25.6)
390(45.3)
150(17.4)
80(9.3)
20(2.3)
3290 3.82 4
Wrong productinformation
160(18.6)
440(51.2)
120(14.0)
100(11.6)
40(4.7)
3160 3.67 10
Ineffectivecommunicationon productsrenewal
100(11.5)
440(50.6)
230(26.4)
60(6.9)
30(3.8)
3100 3.60 12
Poor rewardprograms forloyalty
240(27.9)
380(44.2)
110(12.8)
30(3.5)
100(11.6)
3210 3.73 8
High cost 170(19.8)
540(62.8)
90(10.5)
40(4.7)
20(2.3)
3380 3.93 2
212
Table 5.84 Continued
Nonavailability ofsuitableproducts
220(25.6)
450(52.3)
120(14.0)
30(3.5)
40(4.7)
3360 3.90 3
Better productsby competitor
270(31.4)
440(51.2)
80(9.3)
40(4.7)
30(3.5)
3460 4.02 1
Residence shift 140(16.3)
440(51.2)
200(23.3)
50(5.8)
30(3.5)
3190 3.70 9
Need does notexist anymore
100(11.6)
520(60.5)
90(10.5)
100(11.6)
50(5.8)
3100 3.60 12
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
Table 5.84 provides responses of respondents switching among audio
brands. It is clear that the primary reasons for customers switching among
audio brands are better products by competitor, followed by highly
charged(cost), ‘non availability of suitable products which customer want,
location change by the companies and poor customer service were attributes
are more. Similarly not making the customer feel valued, ‘unsettled customer
complaints, poor reward programs for loyalty are secondary reasons for
switching. Finally wrong product information, undesirable staff and attitude,
ineffective communication on products and need does not exist anymore was
found to the other reasons to switch. It is expressed that better products by
competitors are the primary reason for audio brands respondents shifting from
their brands.
5.5.1.2 Factor Considered while Switching over to other Washing
machines Brands
Table 5.85 shows various factors that are considered for respondents to
switch over to other washing machine brands are given in column 1 and
columns 2 to 6 shows rating scales.
213
REASONS FOR SWITCHING AMONG WASHING MACHINE
BRANDS
Table 5.85
Factors(1)
Stronglyagree
(2)
Agree(3)
Neutral(4)
Disagree(5)
Stronglydisagree
(6)
Totalscore
Averagemean Rank
Unsettledcustomercomplaints
410(45.1)
260(28.6)
180(19.8)
30(3.3)
30(3.3)
3530 4.35 1
Undesirablestaff attitudes
270(29.7)
300(33.0)
210(23.1)
100(11.0)
30(3.3)
3150 3.88 8
Not making thecustomers feelvalued
340(37.4)
400(44.0)
100(11.0)
50(5.5)
20(2.2)
3270 4.03 2
Poorrespondentsservice
290(31.9)
490(53.8)
30(3.3)
50(5.5)
50(5.5)
3220 3.97 4
Locationchange
190(20.9)
460(50.5)
180(19.8)
40(4.4)
40)(4.4)
3010 3.71 12
Wrong productinformation
230(25.3)
440(48.4)
90(9.9)
120(13.2)
30(3.3)
3180 3.92 7
Ineffectivecommunicationon productsrenewal
250(27.5)
370(40.7)
170(18.7)
60(6.6)
60(6.6)
3140 3.87 9
Poor rewardprograms forloyalty
290(31.9)
360(39.6)
100(11.0)
80(8.8)
80(8.8)
2960 3.65 13
High cost 370(40.7)
330(36.3)
120(13.2)
60(5.7)
30(3.3)
3210 3.96 5
Nonavailability ofsuitableproducts
290(31.9)
400(44.0)
120(13.2)
40(4.4)
60(6.6)
3200 3.95 6
Better productsby competitor
270(29.7)
490(53.8)
120(13.2)
20(2.2)
10(1.1)
3260 4.02 3
Residence shift 180(19.8)
400(44.0)
190(20.9)
40(4.4)
100(11.0)
3140 3.87 9
Need does notexist anymore
170(18.7)
450(49.5)
130(14.3)
100(11.0)
60(6.6)
3070 3.79 11
Source: Field Survey and Analysis of Data 2010
Values within brackets show percentage
214
Table 5.85 provides responses of respondents for washing machine
brands. It is clear that the primary reasons for respondents switching among
washing machine brands were ‘unsettled customer complaints, followed by
not making the customer feel valued, better products by competitors, poor
customer service, highly charged(cost) and attributes are more. Secondly ‘non
availability of suitable products which customer wants, wrong product
information, undesirable staff attitude, residence shift was found as reasons.
Finally, ineffective communication on products, location change by the
customer, poor reward programs for loyalty and need do not exist anymore is
found to be the other reasons to switch. It is expressed that better products by
competitors are the primary reasons for washing machine brands respondents
‘unsettled customer complaints ‘shifting from their companies.
5.5.1.3 Factor Considered while Switching over to other White Goods Air
conditioner Brands
Table 5.86 shows various factors for respondents to switch over to
other air conditioner brands which is given in column 1 and columns 2 to 6
show rating scales
REASONS FOR SWITCHING AMONG AIR CONDITIONER BRANDS
Table 5.86
Factors(1)
Stronglyagree(2)
Agree(3)
Neutral(4)
Disagree(5)
Stronglydisagree
(6)
Totalscore
Averagemean
Rank
Unsettledcustomercomplaints
420(51.9)
300(37.0)
50(6.2)
40(4.9)
0 4040 4.25 1
Undesirablestaff attitudes
230(28.4)
390(48.1)
90(8.6)
70(8.6)
30(3.7)
3670 3.86 6
Not making thecustomer feelvalued
250(30.9)
430(53.1)
60(7.4)
50(6.2)
20(2.5)
3830 4.03 2
Poorrespondentsservice
240(29.6)
430(53.1)
60(7.4)
40(4.9)
40(4.9)
3720 3.91 4
215
Table 5.86 Continued
Locationchange
160(19.8)
430(53.1)
100(12.3)
70(8.6)
50(6.2)
3540 3.72 11
Wrong productinformation
250(30.9)
350(43.2)
140(17.3)
40(4.9)
30(3.7)
3630 3.82 8
Ineffectivecommunicationon productsrenewal
230(28.4)
350(43.2)
160(19.8)
40(4.9)
30(3.7)
3570 3.75 10
Poor rewardprograms forloyalty
200(24.7)
350(43.2)
100(12.3)
100(12.3)
60(7.4)
3590 3.77 9
High cost 230(28.4)
420(40.0)
90(11.1)
40(4.9)
30(3.7)
3540 3.72 11
Nonavailability ofsuitableproducts
220(27.2)
450(55.6)
50(6.2)
60(7.4)
30(3.7)
3680 3.87 5
Better productsby competitor
240(29.6)
430(53.1)
60(7.4)
80(9.9)
0 3790 3.98 3
Residence shift 170(21.0)
470(58.0)
100(12.3)
40(4.9)
30(3.7)
3540 3.72 11
Need does notexist anymore
230(28.4)
360(44.4)
100(12.3)
60(7.4)
60(7.4)
3640 3.83 7
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
Table 5.86 provides responses of respondents switching over air
conditioner brands among other brands. It is clears that the primary reasons for
respondents switching among air conditioners are ‘unsettled customer
complaints, followed by not making the customer feel valued, better products
by competitor, poor customer service, non availability of suitable products
which customer want and undesirable staff attitude were more, secondly need
does not exist anymore, wrong product information, poor reward programs for
loyalty is found to be the reasons. Finally, ineffective communication on
products, location change by the customer, highly charged (cost),’ residence
shift’ is found to be the other reasons to switch. It is expressed that better
products by competitors was also the primary reason for air conditioner
respondents ‘unsettled customer complaints shifting from their companies.
216
5.5.1.4Factor Considered to Switching over to other Refrigerator Brands
Table 5.87 shows various factors that were considered for customer to
switch over to other white goods refrigerator brands as given in the column 1
and columns 2 to 6 show rating scales.
REASONS FOR SWITCHING AMONG REFRIGERATOR BRANDS
Table 5.87
Factors(1)
Stronglyagree(20
Agree(3)
Neutral(4)
Disagree(5)
Stronglydisagree
(6)
Totalscore
Averagemean Rank
Unsettledcustomerscomplaints
460(48.4)
340(35.8)
90(9.5)
50(5.3)
10(1.1)
3720 4.08 1
Undesirablestaff attitudes
300(31.6)
380(40.0)
160(16.8)
60(6.3)
50(5.3)
3410 3.74 11
Not making thecustomers feelvalued
330(34.7)
450(47.4)
90(9.5)
30(3.2)
50(5.3)
3720 4.08 2
Poorrespondentsservice
270(28.4)
500(52.6)
80(8.4)
30(3.2)
70(7.4)
3650 4.01 5
Locationchange
210(22.1)
430(45.3)
180(18.9)
100(10.5)
30(3.2)
3450 3.79 7
Wrong productinformation
180(18.9)
570(60.0)
100(10.5)
50(5.3)
50(5.3)
3450 3.79 7
Ineffectivecommunicationon productsrenewal
260(27.4)
410(43.2)
150(15.8)
50(5.3)
80(8.4)
3420 3.75 10
Poor rewardprograms forloyalty
240(25.3)
460(48.4)
120(12.6)
60(6.3)
70(7.4)
3430 3.76 9
High cost 200(21.1)
470(49.5)
170(17.9)
40(4.2)
70(7.4)
3680 4.04 4
Nonavailability ofsuitableproducts
270(28.4)
460(48.4)
100(10.5)
70(7.4)
50(5.3)
3550 3.90 6
Better productsby competitor
320(33.7)
450(47.4)
90(9.5)
30(3.2)
60(6.3)
3720 4.08 2
Residence shift 250(26.3)
390(41.1)
160(16.8)
100(10.5)
50(5.3)
3250 3.57 13
Need does notexist anymore
270(28.4)
440(46.3)
120(12.6)
50(5.3)
70(7.4)
3300 3.62 12
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
217
Table 5.87 provides responses for refrigerator brands respondents
switching among other brands. It is clears that the primary reasons for
respondents switching among other brands are ‘unsettled customer complaints,
followed by not making the customer feel valued, better products by
competitor, highly charged (cost), poor customer service, non availability of
suitable products which customer want, where attributes are more, Secondly
location change by the customer, wrong product information, poor reward
programs for loyalty is found to be the reasons. Finally, ineffective
communication on products, undesirable staff attitudes need does exist
anymore, residence shift was also found to be the other reasons to switch. It is
expressed that better products by competitors is the primary reason for
refrigerator brands customer ‘unsettled customer complaints shifting from
their companies
5.6 RELATIONSHIP BETWEEN CUSTOMER SATISFACTION,
CUSTOMER LOYALTY AND CUSTOMER RETENTION: GAP
ANANLYSIS – SLR MODEL
To understand the CRM practices on consumer durable white goods,
this study attempted to identify the extent to which satisfaction influences
loyalty and whether there exists any relationship between satisfaction and
retention and also what type of relationship exists. In other words, if customers
are satisfied, would that lead to loyalty towards the service provider and
whether the service provider would succeed in retaining them?
Table 5.88
Gap Analysis between Expectations and Satisfaction
Factors
Audio brandsMean
difference
Washing machine brands Meandiffere
nce
Air conditionerbrands
MdiffeExpectations
meansatisfaction
meanExpectations
meansatisfaction
mean
Expectationsmean
satisfactionmean
Overall quality 4.52 4.41 -0.11 4.63 4.33 -0.30 4.69 4.16 -0Worthiness 4.31 3.93 -0.38 4.49 4.07 -0.42 4.46 3.94 -0Responsiveness 4.03 3.92 -0.11 4.15 4.01 -0.14 4.32 4.05 -0Warranty 4.14 3.92 -0.22 4.44 4.33 -0.11 4.38 3.94 -0Pre-sales 3.81 3.87 +0.06 4.00 3.79 -0.21 3.85 3.81 -0After sales service 4.19 3.83 -0.36 4.30 4.00 -0.30 4.20 3.81 -0Loyalty program 3.67 3.70 +0.03 3.69 3.76 +0.07 3.75 3.73 -0Salesperson 3.85 3.85 -0.00 4.18 3.81 -0.37 3.91 3.70 -0Repair 4.05 3.76 -0.29 4.26 3.81 -0.45 4.23 3.85 -0Reliability 4.15 3.99 -0.16 4.41 3.86 -0.55 4.31 3.96 -0customers service 4.29 3.84 -0.45 4.55 3.90 -0.65 4.47 3.75 -0Productcompatibility 4.03 3.88 -0.15 4.08 4.03 -0.05 3.98 4.05 +0Competitive price 3.95 3.79 -0.16 3.98 3.97 -0.01 4.11 4.12 +0
219
It is found that, mean difference between the expectations and
satisfaction do not match in many factors except pre-sales (+0.06), loyalty
program (+0.03), the expectations are high but satisfaction in audio brands are
comparatively lesser and in the washing machine brands except loyalty
programs (+0.07) all other factor are not up to the expectations of respondents
in satisfying the customers. Product compatibility (+0.07) and competitive
price (+0.01), are the two factors higher than their expectations, other factors
are not up to the mark to fulfill the customer needs. In refrigerator brands pre-
sales (+0.03) and loyalty programs (+0.10) are more than what they expect and
other factors unfulfilled the customer’s satisfaction. There is a general
perception that out of 14 factors pre-sales and loyalty programs are the two
factors just above the expectations and all other factors in white goods are not
up to their expectations.
RELATIONSHIP BETWEEN SATISFACTION AND EXPECTATIONS FORAUDIO BRANDS
Figure 5.22
The chart 5.22 shows expectations associated with various criteria’s. It
is observed from the findings, satisfaction on various criteria does not match
the expectations of the respondents. This could lead to reduction in satisfaction
with a tendency towards dissatisfaction. The audio brand providers should
wake up to potential threat.
0123456789
10
1 2 3 4 5 6 7 8 9 10 11 12 13Mean value
Expectation meanSatisfaction mean
220
RELATIONSHIP BETWEEN SATISFACTION AND EXPECTATIONS
FOR WASHING MACHINE BRANDS
Figure 5.23
The chart 5.23 shows expectations associated with various criteria’s. It
is observed from the findings that satisfaction on various criteria’s does not
match the expectations of the respondents. This could lead to reduction in
satisfaction with a tendency towards dissatisfaction. The washing machine
brands providers should wake up to potential threat
0
2
4
6
8
10
1 2 3 4 5 6 7 8 9 10 11 12 13
Mean value
Para
met
ers
Satisfaction meanExpectation mean
221
Figure 5.24
RELATIOSNHIP BETWEEN SATISFACTION AND EXPECTATIONS
FOR AIR CONDITIONER BRANDS
The chart 5.24 shows expectations associated with various criteria’s. It
is observed from the findings satisfaction on various criteria’s does not match
the expectations of the respondents. This could lead to reduction in satisfaction
with a tendency towards dissatisfaction. The air conditioner brands providers
should wake up to potential threat
0
2
4
6
8
10
1 2 3 4 5 6 7 8 9 10 11 12 13
Mean value
ParametersSatisfaction meanExpectationsmean
222
Figure 5.25
RELATIONSHIP BETWEEN SATISFACTION AND EXPECTATIONS
FOR REFRIGERATOR BRANDS
The chart 5.25 shows expectations associated with various criteria’s. It
is observed from the findings satisfaction on various criteria’s does not match
the expectations of the respondents. This could lead to reduction in satisfaction
with a tendency towards dissatisfaction. The refrigerator brands providers
should wake up to potential threat
5.7 CORRELATION BETWEEN CUSTOMER SATISFACTION &
CUSTOMER LOYALTY
5.7.1 Relationship between the Satisfaction and Loyalty for Consumer
Durable White goods
Table 5.89 depicted results of Pearson’s correlation between customer
satisfaction and loyalty towards various criteria’s considered in the decision
making process of selecting a durable white good, Pearson’s correlation’s are
used to test the hypotheses.
0
2
4
6
8
10
1 2 3 4 5 6 7 8 9 10 11 12 13
Mean value
ParameterSatisfaction meanExpectations mean
223
Hypothesis 5
H0: There is no significant relationship between the level of satisfaction and
loyalty of various attributes of white goods.
Table 5.89
RELATIONSHIP BETWEEN CUSTOMER SATISFACTION &
LOYALTY
CustomerSatisfaction &
Loyalty
Audio brands Washing machinebrands
Air conditionerbrands
Refrigeratorbrands
Satisfactionvalue
Loyaltyvalue
Satisfactionvalue
Loyaltyvalue
Satisfactionvalue
Loyaltyvalue
Satisfactionvalue
Loyaltyvalue
Satisfactionvalue
Pearsoncorrelation 1.000 .955** 1.000 .920** 1.000 .947** 1.000 .361**
Sig.(2-tailed) .001 .001 .001 .001
N (1050)
Loyaltyvalue
Pearsoncorrelation .955** 1.000 .920** 1.000 .947** 1.000 .361** 1.000
Sig. (2-tailed) .001 .001 .001 .001
N (1050)
**. Correlation is significant at the 0.01 level (2-tailed).
In table 5.89 it is seen that, there is a strong positive relationship
between customer satisfaction and loyalty attached to various criteria’s while
selecting consumer durable white goods for repeat purchases. Pearson’s
correlation indicated high relationship between all predictor variables of
satisfaction and their relative loyalty except refrigerator brands. This implied a
high degree of positive correlation between loyalty and satisfaction ratings in
the audio, washing machine and air conditioner brands and low degree
positive correlation in the refrigerator brands. Therefore hypotheses Ho is
224
rejected. Hence there is a significant relationship between the level of
satisfaction and loyalty of various attributes of white goods.
CORRELATION BETWEEN SATISFACTION & RETENTION
5.7.2 The Relationship between the Satisfaction and Retention for
Durable White goods
Table 5.90 depicted results of Pearson’s correlation between customer
satisfaction and retention towards various criteria’s considered in the decision
making process of selecting a consumer durable white good, Pearson’s
correlation’s are used to test the hypotheses.
Hypothesis 6
H0: There is no significant relationship between the level of satisfaction and
retention of various attributes.
RELATIONSHIP BETWEEN CUSTOMER SATISFACTION & RETEN
Table 5.90
Customer Satisfaction &Retention
Audio brands Washing machine brands Air conditioner b
Satisfactionvalue
Retentionvalue
Satisfactionvalue
Retentionvalue
Satisfactionvalue
Reteva
Satisfaction value Pearsoncorrelation 1000 .964** 1.000 .961** 1.000 .9
Sig. (2-tailed) .001 .001 .0
N (1050)
Retentionvalue
Pearsoncorrelation .964** 1.000 .961** 1.000 .977** 1
Sig. (2-tailed) .001 .001 .001
N (1050) 1050**. Correlation is significant at the 0.01 level (2-tailed).
226
In table 5.90 it is seen that, there is a strong positive relationship
between satisfaction and retention attached to various criteria’s while selecting
white goods for repeat purchases. Pearson’s correlation indicated high degree
positive relationship between all the predictor variables of satisfaction and
their relative retention. This implied a high degree of relationship between the
retention and satisfaction ratings in audio, washing machine and air
conditioner brands and low degree positive relationship in the refrigerator
brands. Therefore Ho is rejected. Hence there is a significant positive
relationship between satisfaction and retention
CORRELATION BETWEEN LOYALTY & RETENTION
5.7.3 The Relationship between the Loyalty and Retention for Consumer
Durable White goods
Table 5.91 depicted results of Pearson’s correlation between customer
loyalty and retention towards various criteria’s considered in the decision
making process of selecting a durable white good, pearson’s correlation’s are
used to test the hypotheses.
Hypothesis 5
H7: There is no significant relationship between the retention and loyalty of
various attributes.
227
RELATIONSHIP BETWEEN CUSTOMER LOYALTY AND RETENTION
Table 5.91
In table 5.91 it is seen that, there is a high degree of positive
relationship between customer’s retention and loyalty to various criteria’s
while selecting the durable goods for repeat purchases. Pearson’s correlation
indicated high degree of positive relationship between all predictor variables
of retention and loyalty. This implied a high degree of positive relationship
between loyalty and retention ratings in the audio, washing machine, air
conditioner and refrigerator brands. Therefore Ho is rejected. Hence there is a
significant relationship between loyalty and retention of various attributes.
Customerloyalty & retention
Audio brands Washing machinebrands
Air conditionerbrands
Refrigeratorbrands
Loyaltyvalue
Retentionvalue
Loyaltyvalue
Retentionvalue
Loyaltyvalue
Retentionvalue
Loyaltyvalue
Retentionvalue
Loyaltyvalue
Pearsoncorrelation 1.000 .967** 1.000 .915** 1.000 .963** 1.000 .955**
Sig.(2-tailed) .001 .001 .001 .001
N
Retentionvalue
Pearsoncorrelation .967** 1.000 .915** 1.000 .963** 1.000 .955** 1.000
Sig.(2-tailed) .001 .001 .001 .001
N 1050
**. Correlation is significant at the 0.01 level (2-tailed).
228
5.8 PERCEPTION ON CONSUMER DURABLE WHITE GOODS
With a view of understanding better the role of CRM in the consumer
durable white goods services, this study felt the need to know the perception
of consumer durable white goods customer on some accepted beliefs. Table
5.92-5.98 indicates the perception of respondents on consumer durable white
goods.
5.8.1 Perception of Respondents on Various Criteria for Audio Brands
The customer’s perception on various criteria’s for audio brands is
given in column 1 and ratings shown in columns 2 to 6.
Table: 5.92
PERCEPTION CRITERIA ON VARIOUS BRANDS OF AUDIO
S.NCriteria(1)
Stronglyagree
(2)
Agree(3)
Neutral(4)
Disagree(5)
Stronglydisagree
(6)
Totalscore
Mean Rank
1 Directinteractionwith thecompany isbetter thandealingthroughretailers.
350(40.7)
260(30.2)
170(19.8)
40(4.7)
40(4.7) 3420 3.97 1
2 customeralwaysspeak outtheirproblems
160(18.6)
510(59.3)
110(12.8)
70(8.1)
10(1.2)
3320 3.86 2
3 Mostdissatisfiedcustomerleave thebrandswithoutcomplaining
110(12.8)
520(60.5)
140(16.3)
50(5.8)
40(4.7)
3190 3.70 6
229
Table 5.92 Continued
4 customerremain dueto high costof shifting
180(20.9)
470(54.7)
120(14.0)
60(7.0)
30(3.5)
3290 3.82 3
5 Satisfiedcustomerwill notdefect
190(22.1)
400(46.5)
200(23.3)
60(7.0)
10(1.2)
3280 3.81 4
6 One singlecomplaintcan makecustomermove toother brands
110(12.8)
480(55.8)
150(17.4)
70(8.1)
50(5.8)
3110 3.61 7
7 Retailersinfluencesto select thebrands
170(19.8)
460(53.5)
160(18.6)
40(4.7)
30(3.5)
3280 3.81 4
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
Table 5.92 shows the responses of white goods audio brands. From this
respondents perceived ‘direct interaction with the company is better than
dealing through retailers’. It is understood that customers always speak out
their problems. A large majority also feel that ‘customer remains silent due to
high cost of shifting”. Again as predicted there is a strong opinion that
“satisfied customers will not defect”. It is also felt that by a considerable
percentage of durable white goods respondents whom are influenced to select
the brands by retailers. Taking into consideration the perception of all the
respondents, the general conclusion is that ’direct interaction with the
company is better than dealing through retailers” which in turn would lead to
customer loyalty
230
5.8.2 Perception of Respondents on Various Criteria for Washing
machine Brands
Customer’s perceptions on various criteria’s of white goods washing
machine brands are given in column 1 and ratings are given in columns 2 to 6.
Table: 5.93
PERCEPTION ON VARIOUS BRANDS OF WASHING MACHINE
S.N Criteria(1)
Stronglyagree
(2)
Agree(3)
Neutral(4)
Disagree(5)
Stronglydisagree
(6)
Totalscore Mean Rank
1 Directinteractionwith thecompany isbetter thandealingthroughretailers.
410(44.6)
350(38)
80(8.7)
30(3.3)
50(5.4) 3750 4.12 1
2 Customeralways speakout theirproblems
330(36.3)
370(40.7)
120(13.2)
80(8.8)
10(1.1) 3660 4.02 2
3 Mostdissatisfiedcustomersleave thebrands withoutcomplaining
260(28.6)
470(51.6)
100(11.0)
50(5.5)
30(3.3) 3610 3.96 3
4 Customersremain due tohigh cost ofshifting
150(16.5)
470(51.6)
200(22.0)
80(8.8)
10(1.1) 3400 3.73 7
5 Satisfiedcustomers willnot defect
240(26.4)
440(48.4)
180(19.8)
50(5.5) 0 3600 3.95 4
6` One singlecomplaint canmakecustomermove to otherbrands
190(20.9)
470(51.6)
130(14.3)
80(8.8)
40(4.4) 3420 3.75 6
7 Retailersinfluences toselect thebrands
220(24.2)
450(49.5)
100(11.0)
90(9.9)
50(5.5) 3430 3.76 5
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
231
Table 5.93 gives responses of respondents for white goods washing
machine brands. Respondents feel that ‘direct interaction with the company is
better than dealing through retailers’, customer always speak out their
problems”. But at the same time these are found to be top in total scores
ranking. A large majority also felt that ‘most dissatisfied customer leave the
brands without complaining, It is also felt that by a considerable percentage
that satisfied customers will not defect and influence to select the brands by
retailers. Finally the general perception is that, ‘one single complaint can make
customer move to other brands’. Taking into consideration the overall
perception of all the respondents, the general conclusion is that “direct
interaction with the company is better than dealing through retailers” which
would in turn lead to loyalty.
5.8.3 Perception of the Respondents on Various Criteria for Air
conditioner Brands
Customer’s perception on various criteria’s for white goods air
conditioner brands are given in column 1 and ratings are given in columns 2
to 6.
TABLE 5.94
PERCEPTION ON VARIOUS BRANDS OF AIR CONDITIONER
S.N Criteria(1)
Stronglyagree
(2)
Agree(3)
Neutral(4)
Disagree(5)
Stronglydisagree
Totalscore Mean rank
1 Directinteractionwith thecompany isbetter thandealingthroughretailers.
350(43.8)
290(36.2)
110(13.8)
30(3.8)
20(2.5) 3320 4.15 1
2 customersalwaysspeak outtheirproblems
250(31.2)
360(45.0)
90(11.2)
80(10.0)
20(2.6) 3140 3.92 4
232
Table 5.94 Continued
3 Mostdissatisfiedcustomersleave thebrandswithoutcomplaining
210(26.2)
410(51.2)
140(17.5)
30(3.8)
10(1.2) 3180 3.97 3
4 Respondentsremain dueto high costof shifting
120(15.0)
490(61.2)
130(16.2)
30(3.8)
30(3.8) 3040 3.80 5
5 Satisfiedcustomerswill notdefect
230(28.8)
400(50.0)
110(13.8)
60(7.5) 0 3200 4.00 2
6` One singlecomplaintcan makecustomerss move toother brands
170(21.2)
400(38.1)
150(18.8)
40(5.0)
40(5.0) 3020 3.77 6
7 Retailersinfluencesto select thebrands
200(25.0)
320(40.0)
190(23.8)
50(6.2)
40(5.0) 2990 3.73 7
Source: Field Survey and Analysis of Data 2010
Values within brackets show percentage
Table 5.94 gives the responses of air conditioner brands. It is found
that’ direct interaction with the company is better than dealing through
retailers.’ A large majority also felt that “customers remain due to high cost of
shifting”. Again as predicted there is a strong opinion that “most dissatisfied
customers leave the brands without complaining. It is also felt that by a
considerable percentage that consumer durable white goods respondents that
‘one single complaint can make customers move to other brands’, and’
retailers influences to select the brands’. Taking in to consideration the overall
perception of all the respondents, the general conclusion is that “direct
interaction with the company is better than dealing through retailers”.
233
5.8.4 Perception of the Respondents on Various Criteria for Refrigerator
Brands
Customer’s perception on the various criteria’s for consumer durable
white goods refrigerator brands are given in column 1 and ratings are given in
columns 2 to 6.
TABLE: 5.95
PERCEPTION ON VARIOUS BRANDS OF REFRIGERATOR
S.N Criteria(1)
Stronglyagree
(2)
Agree(3)
Neutral(4)
Disagree(5)
Stronglydisagree
(6)
Totalscore Mean Rank
1 Directinteraction withthe company isbetter thandealing throughretailers.
330(35.1)
410(43.6)
90(9.6)
40(4.3) 70
(7.4) 3710 3.94 2
2 Respondentsalways speakout theirproblems
300(31.9)
430(45.7)
140(14.9)
60(6.4)
10(1.1) 3770 4.01 1
3 Mostdissatisfiedcustomersleave thebrands withoutcomplaining
220(23.4)
480(51.1)
180(19.1)
40(4.3)
20(2.1) 3660 3.89 3
4 Respondentsremain due tohigh cost ofshifting
120(12.8)
570(60.6)
150(16.0)
80(8.5)
20(2.1) 3510 3.73 6
5 Satisfiedcustomerswill not defect
220(23.4)
440(46.8)
180(19.1)
70(7.4)
30(3.2) 3570 3.79 5
6` One singlecomplaint canmakerespondentsmove to otherbrands
220(23.4)
410(43.6)
170(18.1)
100(10.6)
40(4.3) 3490 3.71 7
7 Retailersinfluences toselect thebrands
250(26.6)
420(44.7)
170(18.1)
70(7.4)
30(3.2) 3610 3.84 4
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
234
Table 5.95 gives responses of the consumer durable goods refrigerator
brands. Customer’s perception is that ‘direct interaction with the company is
better than dealing through retailers, customer always speak out their
problems. But at the same time these are found to be the top in total scores
ranking. A large majority also felt that “customers always speak out their
problems”, Again as predicted there is a strong opinion that “most dissatisfied
customers leave the brands without complaining ‘retailers influence to select
the brands. It is also felt that by a considerable percentage that satisfied
customers will not defect. One single complaint can make customers move to
other brands. Taking into consideration the overall perception of all the
respondents, the general conclusion is that “direct interaction with the
company is better than dealing through retailers”.
Surprisingly, General perceptions of white goods is that, one single
complaint can make customers move to other brands are not perceived as high.
The Indian customers appear to be more resilient. They do not seem to agree
that one single complaint makes customers move to other companies. There
are not many takers for the view that customers stay back with the company
due to high cost of shifting. It is found that most dissatisfied customers leave
the brands without complaining. The general perception is that retailers
influence to select the brands, there is also a feeling that single product holders
shift company more easily than multiple product holders and that satisfied
product would not defect easily. It is also found that customers always speak
out their problems.
5.9 CUSTOMERS SERVICE
Table 5.96 shows the problem faced by the white goods respondents.
235
Table 5.96
OPINION ON SERVICE
Responses Audiobrands
Washingmachine brands
Airconditioner
brands
Refrigeratorbrands
Experiencedwith problem
Yes 590
(69.4)
660
(72.5)
590
(74.6)
700
(75.3)
No 260
(30.6)
250
(27.5)
200
(25.4)
230
(24.7)
Total (1050) (100) (100) (100) (100)
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
Table 5.96 indicates that in audio brands respondents having service
related problem of 69.4 per cent. 72.5 per cent of the respondents have service
related problem with washing machine brands, air conditioner respondents
have 74.6 per cent problem in service and refrigerator brand respondents have
75.3 per cent. More than one fourth (25 to 30 percent) of all white goods
respondents feels that problems is not found.
Table 5.97 shows how the respondents were rectified under service
related problem with different factors.
236
Table 5.97
RELATIONSHIP ON CUSTOMER SERVICE OF
VARIOUS WHITE GOODS
Customers ServiceAudiobrands
Washingmachinebrands
Airconditioner
brands
Refrigeratorbrands
Mode of contactpreferred most
In person 100(16.9)
110(16.7)
90(15.3)
240(34.3)
Throughcustomerscare
380(64.4)
220(40.9)
240(40.6)
280(40.0)
Internet 60(10.2)
100(15.2)
90(15.3)
80(11.4)
Dealer/retailerby telephone
50(8.5)
230(34.8)
180(30.5)
100(14.3)
Problem resolved
Immediate 50(8.5)
130(19.7)
90(15.3)
290(41.4)
Less than aday
110(18.6)
230(34.8)
230(39.0)
150(21.4)
Between 2and 3 days
280(47.5)
80(12.1)
50(8.5)
90(12.9)
Between 3and 5 days
60(10.2).
20(3.0)
90(15.3)
60(8.6)
More than aweek
90(15.3)
200(30.3)
130(22.0)
110(15.7)
Number of timescontacted
Once 60(10.2)
250(37.9)
100(16.9)
290(41.4)
Twice 260(44.1)
210(31.8)
290(49.2)
120(17.1)
Three times 100(16.9)
110(16.7)
80(13.6)
150(21.4)
More than 3 170(28.8)
90(13.6)
120(20.3)
140(20.0)
Source: Field Survey and Analysis of Data 2010 Values within brackets show percentage
237
A: AUDIO BRANDS
Out of 1,050 surveyed, 64.4 per cent of the respondent’s contacting
through customer care to register brand complaints and 8.5 per cent of the
respondents are contacting through retailers/dealers. Nearly half (47.5 per
cent) of the respondents problems are resolved between 2 to 3 days and it is
observed that only 8.5 per cent problems are solved immediately by the
companies. It is observed that 44.1 per cent of the respondents make contact
with customers care in 2 different times. But (10.2 percent) of the respondents
are contacting company for service related problems in one time.
B: WASHING MACHINE BRANDS
More than two fifth (40.9 per cent) of the respondents are contacting
through customer care to register their service problem and 15.2 per cent are
contacting through internet (i.e. sending massage through electronic-
mail).More than one third (34.8 per cent) of the respondents feel problems
resolved less than a day and only 3.0 per cent problems solved between 3 and
5 days. It is observed that (37.9 per cent) of the respondents feel quit enough
to contact customer care or company one time. (13.6 percent) of the
respondents contacting the service related problems are more than 3 times.
C: AIR CONDITIONER BRANDS
It is found that two fifth (40.6 per cent) of the respondents contacting
through customer care to register service problem and 15.2 per cent are
contacting through internet and in person. It is observed that problems
resolved by the air conditioner brands by a day (39.0 per cent) and only 8.5
per cent respondents problems are solved between 2 and 3 days. Nearly half
(49.2 per cent) of the respondents think twice to contact customer care to
register the problems. (13.6 percent) of the respondents are contacting
customer care with service related problems 3 times.
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D: REFRIGERATOR BRANDS
It is found that, 40.0 per cent of the respondents are contacting through
customer care to register their problems and 11.4 per cent are contacting
through internet. More than one third (41.4 per cent) of the respondents
problems are resolved immediately and 8.6 per cent of the respondents
problems are solved between 3 and 5 days. More than one third (41.4 per cent)
of the respondents are contacting customer care to register their problems one
time, (17.1 percent) of the respondents contacting the service related problems
twice.
5.10 OPINION ON MARKETERS APPROACH
Table 5.98 shows the different modes of contacts preferred by the
respondents.
Table 5.98
OPINION ON MARKETERS APPROACH
SL.No Mode Frequency Percentage
1. SMS 263 25.12
2. Electronic mail 195 18.62
3. Telephone 157 14.99
4. Post 432 41.27
Total 1047 100.00
Source: Field Survey and Analysis of Data 2010
239
Table 5.98 shows the opinion on marketers approach, 41.27 per cent of
the respondents feel that the firm can update their new offer, new product,
promotional schemes through post. Second was found that through SMS
(25.12 per cent), the firm can reach the customer, electronic-mail (18.62 per
cent) is the ultimate new method to reach the customers and only 14.99 per
cent like to make calls over telephone.